non experimental quantitative research title examples

6.1 Overview of Non-Experimental Research

Learning objectives.

Define non-experimental research, distinguish it clearly from experimental research, and give several examples.
Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world).

Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research.

When to Use Non-Experimental Research

As we saw in the last chapter , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable. It stands to reason, therefore, that non-experimental research is appropriate—even necessary—when these conditions are not met. There are many times in which non-experimental research is preferred, including when:

the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach will suffice. But the two approaches can also be used to address the same research question in complementary ways. For example, Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] .

Types of Non-Experimental Research

Non-experimental research falls into three broad categories: cross-sectional research, correlational research, and observational research.

First, cross-sectional research involves comparing two or more pre-existing groups of people. What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Imagine, for example, that a researcher administers the Rosenberg Self-Esteem Scale to 50 American college students and 50 Japanese college students. Although this “feels” like a between-subjects experiment, it is a cross-sectional study because the researcher did not manipulate the students’ nationalities. As another example, if we wanted to compare the memory test performance of a group of cannabis users with a group of non-users, this would be considered a cross-sectional study because for ethical and practical reasons we would not be able to randomly assign participants to the cannabis user and non-user groups. Rather we would need to compare these pre-existing groups which could introduce a selection bias (the groups may differ in other ways that affect their responses on the dependent variable). For instance, cannabis users are more likely to use more alcohol and other drugs and these differences may account for differences in the dependent variable across groups, rather than cannabis use per se.

Cross-sectional designs are commonly used by developmental psychologists who study aging and by researchers interested in sex differences. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect) rather than a direct effect of age. For this reason, longitudinal studies in which one group of people is followed as they age offer a superior means of studying the effects of aging. Once again, cross-sectional designs are also commonly used to study sex differences. Since researchers cannot practically or ethically manipulate the sex of their participants they must rely on cross-sectional designs to compare groups of men and women on different outcomes (e.g., verbal ability, substance use, depression). Using these designs researchers have discovered that men are more likely than women to suffer from substance abuse problems while women are more likely than men to suffer from depression. But, using this design it is unclear what is causing these differences. So, using this design it is unclear whether these differences are due to environmental factors like socialization or biological factors like hormones?

When researchers use a participant characteristic to create groups (nationality, cannabis use, age, sex), the independent variable is usually referred to as an experimenter-selected independent variable (as opposed to the experimenter-manipulated independent variables used in experimental research). Figure 6.1 shows data from a hypothetical study on the relationship between whether people make a daily list of things to do (a “to-do list”) and stress. Notice that it is unclear whether this is an experiment or a cross-sectional study because it is unclear whether the independent variable was manipulated by the researcher or simply selected by the researcher. If the researcher randomly assigned some participants to make daily to-do lists and others not to, then the independent variable was experimenter-manipulated and it is a true experiment. If the researcher simply asked participants whether they made daily to-do lists or not, then the independent variable it is experimenter-selected and the study is cross-sectional. The distinction is important because if the study was an experiment, then it could be concluded that making the daily to-do lists reduced participants’ stress. But if it was a cross-sectional study, it could only be concluded that these variables are statistically related. Perhaps being stressed has a negative effect on people’s ability to plan ahead. Or perhaps people who are more conscientious are more likely to make to-do lists and less likely to be stressed. The crucial point is that what defines a study as experimental or cross-sectional l is not the variables being studied, nor whether the variables are quantitative or categorical, nor the type of graph or statistics used to analyze the data. It is how the study is conducted.

Figure 6.1 Results of a Hypothetical Study on Whether People Who Make Daily To-Do Lists Experience Less Stress Than People Who Do Not Make Such Lists

Second, the most common type of non-experimental research conducted in Psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable. More specifically, in correlational research , the researcher measures two continuous variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related. Correlational research is very similar to cross-sectional research, and sometimes these terms are used interchangeably. The distinction that will be made in this book is that, rather than comparing two or more pre-existing groups of people as is done with cross-sectional research, correlational research involves correlating two continuous variables (groups are not formed and compared).

Third, observational research is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories.

The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure 6.2 shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) is in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Figure 7.1 Internal Validity of Correlational, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlational studies lower still.

Figure 6.2 Internal Validity of Correlation, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlation studies lower still.

Notice also in Figure 6.2 that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

Key Takeaways

Non-experimental research is research that lacks the manipulation of an independent variable.
There are two broad types of non-experimental research. Correlational research that focuses on statistical relationships between variables that are measured but not manipulated, and observational research in which participants are observed and their behavior is recorded without the researcher interfering or manipulating any variables.
In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.
A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative.
A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received.
A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months.
A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance.
Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵
Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵

Share This Book

Increase Font Size

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

7.1 Overview of Nonexperimental Research

Learning objectives.

Define nonexperimental research, distinguish it clearly from experimental research, and give several examples.
Explain when a researcher might choose to conduct nonexperimental research as opposed to experimental research.

What Is Nonexperimental Research?

Nonexperimental research is research that lacks the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both.

In a sense, it is unfair to define this large and diverse set of approaches collectively by what they are not . But doing so reflects the fact that most researchers in psychology consider the distinction between experimental and nonexperimental research to be an extremely important one. This is because while experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, nonexperimental research generally cannot. As we will see, however, this does not mean that nonexperimental research is less important than experimental research or inferior to it in any general sense.

When to Use Nonexperimental Research

As we saw in Chapter 6 “Experimental Research” , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable and randomly assign participants to conditions or to orders of conditions. It stands to reason, therefore, that nonexperimental research is appropriate—even necessary—when these conditions are not met. There are many ways in which this can be the case.

The research question or hypothesis can be about a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
The research question can be about a noncausal statistical relationship between variables (e.g., Is there a correlation between verbal intelligence and mathematical intelligence?).
The research question can be about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions (e.g., Does damage to a person’s hippocampus impair the formation of long-term memory traces?).
The research question can be broad and exploratory, or it can be about what it is like to have a particular experience (e.g., What is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and nonexperimental approaches is generally dictated by the nature of the research question. If it is about a causal relationship and involves an independent variable that can be manipulated, the experimental approach is typically preferred. Otherwise, the nonexperimental approach is preferred. But the two approaches can also be used to address the same research question in complementary ways. For example, nonexperimental studies establishing that there is a relationship between watching violent television and aggressive behavior have been complemented by experimental studies confirming that the relationship is a causal one (Bushman & Huesmann, 2001). Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974).

Types of Nonexperimental Research

Nonexperimental research falls into three broad categories: single-variable research, correlational and quasi-experimental research, and qualitative research. First, research can be nonexperimental because it focuses on a single variable rather than a statistical relationship between two variables. Although there is no widely shared term for this kind of research, we will call it single-variable research . Milgram’s original obedience study was nonexperimental in this way. He was primarily interested in one variable—the extent to which participants obeyed the researcher when he told them to shock the confederate—and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of single-variable research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the research asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories.)

As these examples make clear, single-variable research can answer interesting and important questions. What it cannot do, however, is answer questions about statistical relationships between variables. This is a point that beginning researchers sometimes miss. Imagine, for example, a group of research methods students interested in the relationship between children’s being the victim of bullying and the children’s self-esteem. The first thing that is likely to occur to these researchers is to obtain a sample of middle-school students who have been bullied and then to measure their self-esteem. But this would be a single-variable study with self-esteem as the only variable. Although it would tell the researchers something about the self-esteem of children who have been bullied, it would not tell them what they really want to know, which is how the self-esteem of children who have been bullied compares with the self-esteem of children who have not. Is it lower? Is it the same? Could it even be higher? To answer this question, their sample would also have to include middle-school students who have not been bullied.

Research can also be nonexperimental because it focuses on a statistical relationship between two variables but does not include the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both. This kind of research takes two basic forms: correlational research and quasi-experimental research. In correlational research , the researcher measures the two variables of interest with little or no attempt to control extraneous variables and then assesses the relationship between them. A research methods student who finds out whether each of several middle-school students has been bullied and then measures each student’s self-esteem is conducting correlational research. In quasi-experimental research , the researcher manipulates an independent variable but does not randomly assign participants to conditions or orders of conditions. For example, a researcher might start an antibullying program (a kind of treatment) at one school and compare the incidence of bullying at that school with the incidence at a similar school that has no antibullying program.

The final way in which research can be nonexperimental is that it can be qualitative. The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. In qualitative research , the data are usually nonnumerical and are analyzed using nonstatistical techniques. Rosenhan’s study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semipublic room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256).

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure 7.1 shows how experimental, quasi-experimental, and correlational research vary in terms of internal validity. Experimental research tends to be highest because it addresses the directionality and third-variable problems through manipulation and the control of extraneous variables through random assignment. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Correlational research is lowest because it fails to address either problem. If the average score on the dependent variable differs across levels of the independent variable, it could be that the independent variable is responsible, but there are other interpretations. In some situations, the direction of causality could be reversed. In others, there could be a third variable that is causing differences in both the independent and dependent variables. Quasi-experimental research is in the middle because the manipulation of the independent variable addresses some problems, but the lack of random assignment and experimental control fails to address others. Imagine, for example, that a researcher finds two similar schools, starts an antibullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” There is no directionality problem because clearly the number of bullying incidents did not determine which school got the program. However, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying.

Experiments are generally high in internal validity, quasi-experiments lower, and correlational studies lower still.

Notice also in Figure 7.1 that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well designed quasi-experiment with no obvious confounding variables.

Key Takeaways

Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both.
There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables. Correlational and quasi-experimental research focus on a statistical relationship but lack manipulation or random assignment. Qualitative research focuses on broader research questions, typically involves collecting large amounts of data from a small number of participants, and analyzes the data nonstatistically.
In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.

Discussion: For each of the following studies, decide which type of research design it is and explain why.

A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative.
A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received.
A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months.
A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance.

Bushman, B. J., & Huesmann, L. R. (2001). Effects of televised violence on aggression. In D. Singer & J. Singer (Eds.), Handbook of children and the media (pp. 223–254). Thousand Oaks, CA: Sage.

Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row.

Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258.

Research Methods in Psychology Copyright © 2016 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 7: Nonexperimental Research

Overview of Nonexperimental Research

Learning Objectives

Define nonexperimental research, distinguish it clearly from experimental research, and give several examples.
Explain when a researcher might choose to conduct nonexperimental research as opposed to experimental research.

What Is Nonexperimental Research?

Nonexperimental research is research that lacks the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both.

In a sense, it is unfair to define this large and diverse set of approaches collectively by what they are not . But doing so reflects the fact that most researchers in psychology consider the distinction between experimental and nonexperimental research to be an extremely important one. This distinction is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, nonexperimental research generally cannot. As we will see, however, this inability does not mean that nonexperimental research is less important than experimental research or inferior to it in any general sense.

When to Use Nonexperimental Research

As we saw in Chapter 6 , experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable and randomly assign participants to conditions or to orders of conditions. It stands to reason, therefore, that nonexperimental research is appropriate—even necessary—when these conditions are not met. There are many ways in which preferring nonexperimental research can be the case.

The research question or hypothesis can be about a single variable rather than a statistical relationship between two variables (e.g., How accurate are people’s first impressions?).
The research question can be about a noncausal statistical relationship between variables (e.g., Is there a correlation between verbal intelligence and mathematical intelligence?).
The research question can be about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions (e.g., Does damage to a person’s hippocampus impair the formation of long-term memory traces?).
The research question can be broad and exploratory, or it can be about what it is like to have a particular experience (e.g., What is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and nonexperimental approaches is generally dictated by the nature of the research question. If it is about a causal relationship and involves an independent variable that can be manipulated, the experimental approach is typically preferred. Otherwise, the nonexperimental approach is preferred. But the two approaches can also be used to address the same research question in complementary ways. For example, nonexperimental studies establishing that there is a relationship between watching violent television and aggressive behaviour have been complemented by experimental studies confirming that the relationship is a causal one (Bushman & Huesmann, 2001) [1] . Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [2] .

Types of Nonexperimental Research

As these examples make clear, single-variable research can answer interesting and important questions. What it cannot do, however, is answer questions about statistical relationships between variables. This detail is a point that beginning researchers sometimes miss. Imagine, for example, a group of research methods students interested in the relationship between children’s being the victim of bullying and the children’s self-esteem. The first thing that is likely to occur to these researchers is to obtain a sample of middle-school students who have been bullied and then to measure their self-esteem. But this design would be a single-variable study with self-esteem as the only variable. Although it would tell the researchers something about the self-esteem of children who have been bullied, it would not tell them what they really want to know, which is how the self-esteem of children who have been bullied compares with the self-esteem of children who have not. Is it lower? Is it the same? Could it even be higher? To answer this question, their sample would also have to include middle-school students who have not been bullied thereby introducing another variable.

The final way in which research can be nonexperimental is that it can be qualitative. The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. In qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s study of the experience of people in a psychiatric ward was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semipublic room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256). [3] Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure 7.1 shows how experimental, quasi-experimental, and correlational research vary in terms of internal validity. Experimental research tends to be highest because it addresses the directionality and third-variable problems through manipulation and the control of extraneous variables through random assignment. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Correlational research is lowest because it fails to address either problem. If the average score on the dependent variable differs across levels of the independent variable, it could be that the independent variable is responsible, but there are other interpretations. In some situations, the direction of causality could be reversed. In others, there could be a third variable that is causing differences in both the independent and dependent variables. Quasi-experimental research is in the middle because the manipulation of the independent variable addresses some problems, but the lack of random assignment and experimental control fails to address others. Imagine, for example, that a researcher finds two similar schools, starts an antibullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” There is no directionality problem because clearly the number of bullying incidents did not determine which school got the program. However, the lack of random assignment of children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying.

Key Takeaways

Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both.
There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables. Correlational and quasi-experimental research focus on a statistical relationship but lack manipulation or random assignment. Qualitative research focuses on broader research questions, typically involves collecting large amounts of data from a small number of participants, and analyses the data nonstatistically.
In general, experimental research is high in internal validity, correlational research is low in internal validity, and quasi-experimental research is in between.

Discussion: For each of the following studies, decide which type of research design it is and explain why.

A researcher conducts detailed interviews with unmarried teenage fathers to learn about how they feel and what they think about their role as fathers and summarizes their feelings in a written narrative.
A researcher measures the impulsivity of a large sample of drivers and looks at the statistical relationship between this variable and the number of traffic tickets the drivers have received.
A researcher randomly assigns patients with low back pain either to a treatment involving hypnosis or to a treatment involving exercise. She then measures their level of low back pain after 3 months.
A college instructor gives weekly quizzes to students in one section of his course but no weekly quizzes to students in another section to see whether this has an effect on their test performance.
Bushman, B. J., & Huesmann, L. R. (2001). Effects of televised violence on aggression. In D. Singer & J. Singer (Eds.), Handbook of children and the media (pp. 223–254). Thousand Oaks, CA: Sage. ↵
Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵
Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵

Research that lacks the manipulation of an independent variable, random assignment of participants to conditions or orders of conditions, or both.

Research that focuses on a single variable rather than a statistical relationship between two variables.

The researcher measures the two variables of interest with little or no attempt to control extraneous variables and then assesses the relationship between them.

The researcher manipulates an independent variable but does not randomly assign participants to conditions or orders of conditions.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

non experimental quantitative research title examples

Market research

Non-experimental research: what is it, features, advantages and examples?

TRY OUT NOW

A very common type of research in areas such as psychology, the measurement of unemployment rates, consumer studies or opinion polls is the non-experimental research .

Learn more about their features, benefits, and when to use them.

1 What is non-experimental research?
2 Characteristics of non-experimental research
3 When is non-experimental research used?
4 Advantages and disadvantages of non-experimental research
5 Types of non-experimental research
6 Examples of non-experimental research
7 Conclusion
8 1:1 Live Online Presentation: QUESTIONPRO MARKET RESEARCH SOFTWARE
9 Try software for market research and experience management now for 10 days free of charge!

What is non-experimental research?

Non-experimental research is the type of research in which there is no independent variable. Instead, the researcher observes the context in which the phenomenon occurs and analyses it to obtain information.

In contrast to experimental research, in which the variables are kept constant, non-experimental research is conducted when the researcher cannot control, manipulate, or change the subjects during the study, but relies on interpretations or observations to reach a conclusion reach. This means that the method cannot rely on correlations, surveys or case studies and cannot demonstrate a true cause-and-effect relationship.

The researchers are not directly involved in the experiment. Since it is an observational method, it is also used for descriptive research.

Characteristics of non-experimental research

Some of the key features of non-experimental research are:

Most studies are based on events that occurred in the past and are analysed retrospectively.
This method does not involve conducting controlled experiments, for example for ethical or moral reasons.
No study samples are created; on the contrary, the samples or participants already exist and are developing in their environment.
The researcher does not intervene directly in the sample's environment.
This method examines phenomena exactly as they occurred.

When is non-experimental research used?

Non-experimental research can be applied in the following cases:

When the research question relates to one variable rather than a statistical relationship between two variables.
In studies where the research question involves a non-causal statistical relationship between variables.
When the research question has a causal relationship but the independent variable cannot be manipulated.
In exploratory or broad-based research that focuses on a specific experience.

Advantages and disadvantages of non-experimental research

Some Benefits of non-experimental research are:

She is very flexible during the research process
The cause of the phenomenon is known and the effect of the phenomenon is being investigated.
The researcher can determine the characteristics of the study group.

All disadvantages include:

The groups are not representative of the entire population.
There may be errors in the methodology that lead to bias.

Non-experimental research is based on the observation of phenomena in their natural environment. This way they can be examined later to reach a conclusion.

Types of non-experimental research

Non-experimental research can take the following forms:

Cross-sectional research : In cross-sectional research, a precise point in time of the study is observed and analysed to capture different study groups or samples. This type of research is divided into:

Descriptive : When values are observed in which one or more variables are represented so that a description of the variables is made when the data is obtained.
Causal research : Its task is to explain the reasons and the relationship that exists between the variables at a certain point in time.

Longitudinal research : In a longitudinal study, researchers attempt to analyse the changes and evolution of the relationships between variables over time. Longitudinal research can be divided into:

trend : when they examine the changes to which the study group is generally exposed. Group development: when the study group is a smaller sample.
Panel : when individual and group changes are analysed to identify the factor that causes them.

Examples of non-experimental research

Examples of non-experimental research include statistical surveys, which survey public opinion on an issue to determine a common viewpoint. Or surveys, where a set of statistical data is available and these are interpreted and organized to obtain as much relevant data as possible.

Another possible example is bibliographic research: consulting bibliographic or newspaper sources, reading previous authors, and presenting the results in a report, essay, or monograph. In this case too, it is not about controlled experiments, but about the professional and/or personal perspective of the author consulted or the researcher himself.

Non-experimental research is one type of research , which does not draw its final conclusions and working data through a series of reproducible actions and reactions in a controlled environment to obtain interpretable results, that is, through experiments. Of course, this does not mean that it is not serious, documented and methodologically rigorous research.

Choosing an experimental or non-experimental research design depends on your goals and resources. If you need help conducting research and collecting relevant data, or have questions about the best approach to your research goals, contact us today. You can create an account with our survey software and use over 88 features, including dashboard and reports, for free.

1:1 live online presentation: QUESTIONPRO MARKET RESEARCH SOFTWARE

Arrange an individual appointment and discover our market research software.

Try software for market research and experience management now for 10 days free of charge!

Do you have any questions about the content of this blog? Simply contact us via contact form . We look forward to a dialogue with you! You too can test QuestionPro for 10 days free of charge and without risk in depth!

Test the agile market research and experience management platform for qualitative and quantitative data collection and data analysis from QuestionPro for 10 days free of charge

FURTHER KEYWORDS

Types of research | Empirical research | Document research

SHARE THIS ARTICLE

KEYWORDS OF THIS BLOG POST

non-experimental research | non-experimental | Research

FURTHER INFORMATION

Applied Research: Definition, Types and Examples
Experimental research: what it is, what types there are and how to carry it out
Types of research and their features
What is exploratory research?
Mixed methods research: what it is and what types there are
Data filtering: what it is, benefits and examples
Data collection tools: which are the best?
Big Data and Artificial Intelligence: How do they work together?

PRESS RELEASES

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Non-Experimental Research

28 Overview of Non-Experimental Research

Learning objectives.

Define non-experimental research, distinguish it clearly from experimental research, and give several examples.
Explain when a researcher might choose to conduct non-experimental research as opposed to experimental research.

What Is Non-Experimental Research?

When to Use Non-Experimental Research

the research question or hypothesis relates to a single variable rather than a statistical relationship between two variables (e.g., how accurate are people’s first impressions?).
the research question pertains to a non-causal statistical relationship between variables (e.g., is there a correlation between verbal intelligence and mathematical intelligence?).
the research question is about a causal relationship, but the independent variable cannot be manipulated or participants cannot be randomly assigned to conditions or orders of conditions for practical or ethical reasons (e.g., does damage to a person’s hippocampus impair the formation of long-term memory traces?).
the research question is broad and exploratory, or is about what it is like to have a particular experience (e.g., what is it like to be a working mother diagnosed with depression?).

Again, the choice between the experimental and non-experimental approaches is generally dictated by the nature of the research question. Recall the three goals of science are to describe, to predict, and to explain. If the goal is to explain and the research question pertains to causal relationships, then the experimental approach is typically preferred. If the goal is to describe or to predict, a non-experimental approach is appropriate. But the two approaches can also be used to address the same research question in complementary ways. For example, in Milgram’s original (non-experimental) obedience study, he was primarily interested in one variable—the extent to which participants obeyed the researcher when he told them to shock the confederate—and he observed all participants performing the same task under the same conditions. However, Milgram subsequently conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study (Milgram, 1974) [1] .

Types of Non-Experimental Research

Non-experimental research falls into two broad categories: correlational research and observational research.

The most common type of non-experimental research conducted in psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable. More specifically, in correlational research , the researcher measures two variables with little or no attempt to control extraneous variables and then assesses the relationship between them. As an example, a researcher interested in the relationship between self-esteem and school achievement could collect data on students’ self-esteem and their GPAs to see if the two variables are statistically related.

Observational research is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. Milgram’s original obedience study was non-experimental in this way. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions. The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. The variable was whether participants “remembered” having experienced mildly traumatic childhood events (e.g., getting lost in a shopping mall) that they had not actually experienced but that the researchers asked them about repeatedly. In this particular study, nearly a third of the participants “remembered” at least one event. (As with Milgram’s original study, this study inspired several later experiments on the factors that affect false memories).

Cross-Sectional, Longitudinal, and Cross-Sequential Studies

When psychologists wish to study change over time (for example, when developmental psychologists wish to study aging) they usually take one of three non-experimental approaches: cross-sectional, longitudinal, or cross-sequential. Cross-sectional studies involve comparing two or more pre-existing groups of people (e.g., children at different stages of development). What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Using this design, developmental psychologists compare groups of people of different ages (e.g., young adults spanning from 18-25 years of age versus older adults spanning 60-75 years of age) on various dependent variables (e.g., memory, depression, life satisfaction). Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable. For instance, differences between the groups may reflect the generation that people come from (a cohort effect ) rather than a direct effect of age. For this reason, longitudinal studies , in which one group of people is followed over time as they age, offer a superior means of studying the effects of aging. However, longitudinal studies are by definition more time consuming and so require a much greater investment on the part of the researcher and the participants. A third approach, known as cross-sequential studies , combines elements of both cross-sectional and longitudinal studies. Rather than measuring differences between people in different age groups or following the same people over a long period of time, researchers adopting this approach choose a smaller period of time during which they follow people in different age groups. For example, they might measure changes over a ten year period among participants who at the start of the study fall into the following age groups: 20 years old, 30 years old, 40 years old, 50 years old, and 60 years old. This design is advantageous because the researcher reaps the immediate benefits of being able to compare the age groups after the first assessment. Further, by following the different age groups over time they can subsequently determine whether the original differences they found across the age groups are due to true age effects or cohort effects.

The types of research we have discussed so far are all quantitative, referring to the fact that the data consist of numbers that are analyzed using statistical techniques. But as you will learn in this chapter, many observational research studies are more qualitative in nature. In qualitative research , the data are usually nonnumerical and therefore cannot be analyzed using statistical techniques. Rosenhan’s observational study of the experience of people in psychiatric wards was primarily qualitative. The data were the notes taken by the “pseudopatients”—the people pretending to have heard voices—along with their hospital records. Rosenhan’s analysis consists mainly of a written description of the experiences of the pseudopatients, supported by several concrete examples. To illustrate the hospital staff’s tendency to “depersonalize” their patients, he noted, “Upon being admitted, I and other pseudopatients took the initial physical examinations in a semi-public room, where staff members went about their own business as if we were not there” (Rosenhan, 1973, p. 256) [2] . Qualitative data has a separate set of analysis tools depending on the research question. For example, thematic analysis would focus on themes that emerge in the data or conversation analysis would focus on the way the words were said in an interview or focus group.

Internal Validity Revisited

Recall that internal validity is the extent to which the design of a study supports the conclusion that changes in the independent variable caused any observed differences in the dependent variable. Figure 6.1 shows how experimental, quasi-experimental, and non-experimental (correlational) research vary in terms of internal validity. Experimental research tends to be highest in internal validity because the use of manipulation (of the independent variable) and control (of extraneous variables) help to rule out alternative explanations for the observed relationships. If the average score on the dependent variable in an experiment differs across conditions, it is quite likely that the independent variable is responsible for that difference. Non-experimental (correlational) research is lowest in internal validity because these designs fail to use manipulation or control. Quasi-experimental research (which will be described in more detail in a subsequent chapter) falls in the middle because it contains some, but not all, of the features of a true experiment. For instance, it may fail to use random assignment to assign participants to groups or fail to use counterbalancing to control for potential order effects. Imagine, for example, that a researcher finds two similar schools, starts an anti-bullying program in one, and then finds fewer bullying incidents in that “treatment school” than in the “control school.” While a comparison is being made with a control condition, the inability to randomly assign children to schools could still mean that students in the treatment school differed from students in the control school in some other way that could explain the difference in bullying (e.g., there may be a selection effect).

Figure 6.1 Internal Validity of Correlational, Quasi-Experimental, and Experimental Studies. Experiments are generally high in internal validity, quasi-experiments lower, and correlational studies lower still.

Notice also in Figure 6.1 that there is some overlap in the internal validity of experiments, quasi-experiments, and correlational (non-experimental) studies. For example, a poorly designed experiment that includes many confounding variables can be lower in internal validity than a well-designed quasi-experiment with no obvious confounding variables. Internal validity is also only one of several validities that one might consider, as noted in Chapter 5.

Milgram, S. (1974). Obedience to authority: An experimental view . New York, NY: Harper & Row. ↵
Rosenhan, D. L. (1973). On being sane in insane places. Science, 179 , 250–258. ↵

A research that lacks the manipulation of an independent variable.

Research that is non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable.

Research that is non-experimental because it focuses on recording systemic observations of behavior in a natural or laboratory setting without manipulating anything.

Studies that involve comparing two or more pre-existing groups of people (e.g., children at different stages of development).

Differences between the groups may reflect the generation that people come from rather than a direct effect of age.

Studies in which one group of people are followed over time as they age.

Studies in which researchers follow people in different age groups in a smaller period of time.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

school Campus Bookshelves
menu_book Bookshelves
perm_media Learning Objects
login Login
how_to_reg Request Instructor Account
hub Instructor Commons
Download Page (PDF)
Download Full Book (PDF)
Periodic Table
Physics Constants
Scientific Calculator
Reference & Cite
Tools expand_more
Readability

selected template will load here

This action is not available.

6: Non-Experimental Research

Last updated
Save as PDF
Page ID 19616

Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton

Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton
Kwantlen Polytechnic U., Washington State U., & Texas A&M U.—Texarkana

In this chapter we look more closely at non-experimental research. We begin with a general definition of, non-experimental research, along with a discussion of when and why non-experimental research is more appropriate than experimental research. We then look separately at three important types of non-experimental research: cross-sectional research, correlational research and observational research.

6.1: Prelude to Nonexperimental Research What do the following classic studies have in common? Stanley Milgram found that about two thirds of his research participants were willing to administer dangerous shocks to another person just because they were told to by an authority figure (Milgram, 1963). Elizabeth Loftus and Jacqueline Pickrell showed that it is relatively easy to “implant” false memories in people by repeatedly asking them about childhood events that did not actually happen to them (Loftus & Pickrell, 1995).
6.2: Overview of Non-Experimental Research Most researchers in psychology consider the distinction between experimental and non-experimental research to be an extremely important one. This is because although experimental research can provide strong evidence that changes in an independent variable cause differences in a dependent variable, non-experimental research generally cannot. As we will see, however, this inability to make causal conclusions does not mean that non-experimental research is less important than experimental research.
6.3: Correlational Research Correlational research is a type of non-experimental research in which the researcher measures two variables and assesses the statistical relationship (i.e., the correlation) between them with little or no effort to control extraneous variables. There are many reasons that researchers interested in statistical relationships between variables would choose to conduct a correlational study rather than an experiment.
6.4: Complex Correlation As we have already seen, researchers conduct correlational studies rather than experiments when they are interested in noncausal relationships or when they are interested in causal relationships but the independent variable cannot be manipulated for practical or ethical reasons. In this section, we look at some approaches to complex correlational research that involve measuring several variables and assessing the relationships among them.
6.5: Qualitative Research Quantitative researchers typically start with a focused research question or hypothesis, collect a small amount of data from a large number of individuals, describe the resulting data using statistical techniques, and draw general conclusions about some large population. Although this method is by far the most common approach to conducting empirical research in psychology, there is an important alternative called qualitative research.
6.6: Observational Research Observational research is used to refer to several different types of non-experimental studies in which behavior is systematically observed and recorded. The goal of observational research is to describe a variable or set of variables. The goal is to obtain a snapshot of specific characteristics of an individual, group, or setting. Observational research is non-experimental because nothing is manipulated or controlled, and as such we cannot arrive at causal conclusions using this approach.
6.7: Non-Experimental Research (Summary) Key Takeaways and Exercises for the chapter on Non-Experimental Research.

Thumbnail: An example of data produced by data dredging, showing a correlation between the number of letters in a spelling bee's winning word (red curve) and the number of people in the United States killed by venomous spiders (black curve). (CC BY 4.0 International; Tyler Vigen - Spurious Correlations ).

Skip to main content
Skip to primary sidebar
Skip to footer
QuestionPro

Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Investigación de mercado

Non-experimental research: What it is, overview & advantages

Non-experimental research is the type of research that lacks an independent variable. Instead, the researcher observes the context in which the phenomenon occurs and analyzes it to obtain information.

Unlike experimental research , where the variables are held constant, non-experimental research happens during the study when the researcher cannot control, manipulate or alter the subjects but relies on interpretation or observations to conclude.

This means that the method must not rely on correlations, surveys , or case studies and cannot demonstrate an actual cause and effect relationship.

Characteristics of non-experimental research

Some of the essential characteristics of non-experimental research are necessary for the final results. Let’s talk about them to identify the most critical parts of them.

Most studies are based on events that occurred previously and are analyzed later.
In this method, controlled experiments are not performed for reasons such as ethics or morality.
No study samples are created; on the contrary, the samples or participants already exist and develop in their environment.
The researcher does not intervene directly in the environment of the sample.
This method studies the phenomena exactly as they occurred.

Types of non-experimental research

Non-experimental research can take the following forms:

Cross-sectional research : Cross-sectional research is used to observe and analyze the exact time of the research to cover various study groups or samples. This type of research is divided into:

Descriptive: When values are observed where one or more variables are presented.
Causal: It is responsible for explaining the reasons and relationship that exists between variables in a given time.

Longitudinal research: In a longitudinal study , researchers aim to analyze the changes and development of the relationships between variables over time. Longitudinal research can be divided into:

Trend: When they study the changes faced by the study group in general.
Group evolution: When the study group is a smaller sample.
Panel: It is in charge of analyzing individual and group changes to discover the factor that produces them.

LEARN ABOUT: Quasi-experimental Research

When to use non-experimental research

Non-experimental research can be applied in the following ways:

When the research question may be about one variable rather than a statistical relationship about two variables.
There is a non-causal statistical relationship between variables in the research question.
The research question has a causal research relationship, but the independent variable cannot be manipulated.
In exploratory or broad research where a particular experience is confronted.

Advantages and disadvantages

Some advantages of non-experimental research are:

It is very flexible during the research process
The cause of the phenomenon is known, and the effect it has is investigated.
The researcher can define the characteristics of the study group.

Among the disadvantages of non-experimental research are:

The groups are not representative of the entire population.
Errors in the methodology may occur, leading to research biases .

Non-experimental research is based on the observation of phenomena in their natural environment. In this way, they can be studied later to reach a conclusion.

Difference between experimental and non-experimental research

Experimental research involves changing variables and randomly assigning conditions to participants. As it can determine the cause, experimental research designs are used for research in medicine, biology, and social science.

Experimental research designs have strict standards for control and establishing validity. Although they may need many resources, they can lead to very interesting results.

Non-experimental research, on the other hand, is usually descriptive or correlational without any explicit changes done by the researcher. You simply describe the situation as it is, or describe a relationship between variables. Without any control, it is difficult to determine causal effects. The validity remains a concern in this type of research. However, it’s’ more regarding the measurements instead of the effects.

LEARN MORE: Descriptive Research vs Correlational Research

Whether you should choose experimental research or non-experimental research design depends on your goals and resources. If you need any help with how to conduct research and collect relevant data, or have queries regarding the best approach for your research goals, contact us today! You can create an account with our survey software and avail of 88+ features including dashboard and reporting for free.

Create a free account

MORE LIKE THIS

The Best Email Survey Tool to Boost Your Feedback Game

May 7, 2024

Top 10 Employee Engagement Survey Tools

15 Best Customer Experience Software of 2024

May 2, 2024

school Campus Bookshelves
menu_book Bookshelves
perm_media Learning Objects
login Login
how_to_reg Request Instructor Account
hub Instructor Commons
Download Page (PDF)
Download Full Book (PDF)
Periodic Table
Physics Constants
Scientific Calculator
Reference & Cite
Tools expand_more
Readability

selected template will load here

This action is not available.

2.5: Experimental and Non-experimental Research

Last updated
Save as PDF
Page ID 3948

Danielle Navarro
University of New South Wales

One of the big distinctions that you should be aware of is the distinction between “experimental research” and “non-experimental research”. When we make this distinction, what we’re really talking about is the degree of control that the researcher exercises over the people and events in the study.

Experimental research

The key features of experimental research is that the researcher controls all aspects of the study, especially what participants experience during the study. In particular, the researcher manipulates or varies the predictor variables (IVs), and then allows the outcome variable (DV) to vary naturally. The idea here is to deliberately vary the predictors (IVs) to see if they have any causal effects on the outcomes. Moreover, in order to ensure that there’s no chance that something other than the predictor variables is causing the outcomes, everything else is kept constant or is in some other way “balanced” to ensure that they have no effect on the results. In practice, it’s almost impossible to think of everything else that might have an influence on the outcome of an experiment, much less keep it constant. The standard solution to this is randomisation: that is, we randomly assign people to different groups, and then give each group a different treatment (i.e., assign them different values of the predictor variables). We’ll talk more about randomisation later in this course, but for now, it’s enough to say that what randomisation does is minimise (but not eliminate) the chances that there are any systematic difference between groups.

Let’s consider a very simple, completely unrealistic and grossly unethical example. Suppose you wanted to find out if smoking causes lung cancer. One way to do this would be to find people who smoke and people who don’t smoke, and look to see if smokers have a higher rate of lung cancer. This is not a proper experiment, since the researcher doesn’t have a lot of control over who is and isn’t a smoker. And this really matters: for instance, it might be that people who choose to smoke cigarettes also tend to have poor diets, or maybe they tend to work in asbestos mines, or whatever. The point here is that the groups (smokers and non-smokers) actually differ on lots of things, not just smoking. So it might be that the higher incidence of lung cancer among smokers is caused by something else, not by smoking per se. In technical terms, these other things (e.g. diet) are called “confounds”, and we’ll talk about those in just a moment.

In the meantime, let’s now consider what a proper experiment might look like. Recall that our concern was that smokers and non-smokers might differ in lots of ways. The solution, as long as you have no ethics, is to control who smokes and who doesn’t. Specifically, if we randomly divide participants into two groups, and force half of them to become smokers, then it’s very unlikely that the groups will differ in any respect other than the fact that half of them smoke. That way, if our smoking group gets cancer at a higher rate than the non-smoking group, then we can feel pretty confident that (a) smoking does cause cancer and (b) we’re murderers.

Non-experimental research

Non-experimental research is a broad term that covers “any study in which the researcher doesn’t have quite as much control as they do in an experiment”. Obviously, control is something that scientists like to have, but as the previous example illustrates, there are lots of situations in which you can’t or shouldn’t try to obtain that control. Since it’s grossly unethical (and almost certainly criminal) to force people to smoke in order to find out if they get cancer, this is a good example of a situation in which you really shouldn’t try to obtain experimental control. But there are other reasons too. Even leaving aside the ethical issues, our “smoking experiment” does have a few other issues. For instance, when I suggested that we “force” half of the people to become smokers, I must have been talking about starting with a sample of non-smokers, and then forcing them to become smokers. While this sounds like the kind of solid, evil experimental design that a mad scientist would love, it might not be a very sound way of investigating the effect in the real world. For instance, suppose that smoking only causes lung cancer when people have poor diets, and suppose also that people who normally smoke do tend to have poor diets. However, since the “smokers” in our experiment aren’t “natural” smokers (i.e., we forced non-smokers to become smokers; they didn’t take on all of the other normal, real life characteristics that smokers might tend to possess) they probably have better diets. As such, in this silly example they wouldn’t get lung cancer, and our experiment will fail, because it violates the structure of the “natural” world (the technical name for this is an “artifactual” result; see later).

One distinction worth making between two types of non-experimental research is the difference be- tween quasi-experimental research and case studies. The example I discussed earlier – in which we wanted to examine incidence of lung cancer among smokers and non-smokers, without trying to control who smokes and who doesn’t – is a quasi-experimental design. That is, it’s the same as an experiment, but we don’t control the predictors (IVs). We can still use statistics to analyse the results, it’s just that we have to be a lot more careful.

The alternative approach, case studies, aims to provide a very detailed description of one or a few instances. In general, you can’t use statistics to analyse the results of case studies, and it’s usually very hard to draw any general conclusions about “people in general” from a few isolated examples. However, case studies are very useful in some situations. Firstly, there are situations where you don’t have any alternative: neuropsychology has this issue a lot. Sometimes, you just can’t find a lot of people with brain damage in a specific area, so the only thing you can do is describe those cases that you do have in as much detail and with as much care as you can. However, there’s also some genuine advantages to case studies: because you don’t have as many people to study, you have the ability to invest lots of time and effort trying to understand the specific factors at play in each case. This is a very valuable thing to do. As a consequence, case studies can complement the more statistically-oriented approaches that you see in experimental and quasi-experimental designs. We won’t talk much about case studies in these lectures, but they are nevertheless very valuable tools!

Non-Experimental Research Methods in Quantitative Research Report (Assessment)

In contrast to experimental research, non-experimental research allows the investigation or examination of variables or phenomena that cannot be manipulated by the researcher, implying that these variables must be studied as they exist since it is often difficult to alter or control them.

Non-experimental research also encompasses studies that do not employ random assignment of respondents to a specified treatment condition (Belli, n.d.). It is the purpose of this paper to identify and discuss some of existing non-experimental research methods and the type of data that could be used in each of the discussed methods.

One of the main rationales for using non-experimental research, according to Belli (n.d.), is that many variables of interest in the field of social science cannot be controlled or manipulated by virtue of the fact that they are attribute variables. For instance, it is difficult for a researcher to manipulate the social economic status, gender, learning style, thinking pattern, or any other personal characteristic of a respondent because these attributes exist naturally.

Another major reason for using non-experimental research comes from the fact that, in some instances, it would be unethical for the researcher to randomly assign respondents to diverse treatment conditions (Punch & Punch, 2005). For instance, it would by unethical for the researcher to study the effects of drug abuse by randomly assigning respondents to either a drug abusing or a non drug abusing group for a specified time-frame.

It is imperative to note that “…in non-experimental research, groups based on different traits or on self-selection, such as being or not being a smoker, may differ for any other reasons other than the variable under investigation” (Belli, n.d., p. 60).

This is not the case in experimental research, which makes use of the process of random assignment to ensure that individuals included in a sample bears similar characteristics except for the treatment condition in which they are placed.

Consensus about the existing typologies of non-experimental research methods has not been forthcoming, and researchers have resulted in categorizing non-experimental research either based on the purpose of the study or the time-frame delegated for data collection (Belli, n.d.). This paper discusses three different typologies of non-experimental research methods based on the purpose of the study.

The first type is known as descriptive non-experimental research method, in which the fundamental concern for the researcher lies in describing some phenomena of interest or documenting its characteristics (Belli, n.d.). This typology is mainly used to document the status quo of a phenomenon under investigation or to perform a needs assessment in an area that interests the researcher.

According to Punch &Punch (2005), descriptive research designs can utilize nominal data (numbers represent categories), ordinal data (numbers indicate rank order of observation), interval data (numbers represent equal units and intervals between observations can be compared), and ratio data (numbers represent equal intervals or units between absolute zero).

These data can be harnessed into frequency distributions, percentages, averages, central tendencies or observed variability to describe the phenomena of interest (What is Statistics, n.d.).

The second typology of non-experimental research methods is known as correlational research design, in which the fundamental concern of the researcher is to describe the statistical relationship between two or more variables obtained from each subject or phenomena of interest (Punch & Punch, 2005).

Most attitudinal and motivation research heavily relies on correlational research designs to describe and compare the variables of interest. It is imperative to note that in correlational research, data on at least two variables must be obtained from each respondent or phenomena of interest.

According to Punch & Punch (2005), correlational non-experimental research designs are mostly used in “…situations where variation occurs in the independent variables of interest, but where it is not possible to manipulate or control that variation for research purposes” (p. 75).

These authors further posit that correlational non-experimental research designs mostly utilize continuous data, artificially or truly dichotomous data, ordinal data (rank-ordered), and nominal data.

The final typology that will be discussed in this paper is known as explanatory non-experimental research. As acknowledged by Punch & Punch (2005), the primary focus of explanatory research designs lies in attempting to explain how some variables of interest works or why it operates.

The underlying objective of the researcher is often to examine or test a theory about a variable or phenomenon of interest. In most occasions, researchers engaging this method formulate a set of hypothesis from the used theoretical or conceptual framework, which are then tested in an attempt to validate the theory.

According to Johnson & Christensen (2011), the explanatory non-experimental research design mostly utilizes ordinal (rank-ordered) and interval data to explain how a particular variable operates the way it does.

Reference List

Belli, G. Non experimental quantitative research . Web.

Johnson, B., & Christensen, L. (2011). Educational research: Quantitative, qualitative, and mixed approaches , 4 th Ed. Thousand Oaks, CA: Sage Publications Inc.

Punch, K.F., & Punch, K. (2005). Introduction to social research: Qualitative & quantitative approaches, 2 nd Ed. Thousand Oaks, CA: Sage Publications Inc.

What is statistics ? Web.

Chicago (A-D)
Chicago (N-B)

IvyPanda. (2023, November 2). Non-Experimental Research Methods in Quantitative Research. https://ivypanda.com/essays/non-experimental-research-methods-in-quantitative-research/

"Non-Experimental Research Methods in Quantitative Research." IvyPanda , 2 Nov. 2023, ivypanda.com/essays/non-experimental-research-methods-in-quantitative-research/.

IvyPanda . (2023) 'Non-Experimental Research Methods in Quantitative Research'. 2 November.

IvyPanda . 2023. "Non-Experimental Research Methods in Quantitative Research." November 2, 2023. https://ivypanda.com/essays/non-experimental-research-methods-in-quantitative-research/.

1. IvyPanda . "Non-Experimental Research Methods in Quantitative Research." November 2, 2023. https://ivypanda.com/essays/non-experimental-research-methods-in-quantitative-research/.

Bibliography

IvyPanda . "Non-Experimental Research Methods in Quantitative Research." November 2, 2023. https://ivypanda.com/essays/non-experimental-research-methods-in-quantitative-research/.

Experimental, Quasi-Experimental and Nonexperimental Research in Health Care
Quasi-, Non-, and Experimental Research Types
Non- and Experimental and Research Designs
Scientific and Pseudoscientific Claims
Living Environments and Its Correlation With Human Diseases
Citrus Greening Disease in The United States
Importance of the Cultural Competence in Nursing
Multicultural Influences on Australian Cuisine

Home » 500+ Quantitative Research Titles and Topics

500+ Quantitative Research Titles and Topics

Table of Contents

Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology , economics , and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas to explore, from analyzing data on a specific population to studying the effects of a particular intervention or treatment. In this post, we will provide some ideas for quantitative research topics that may inspire you and help you narrow down your interests.

Quantitative Research Titles

Quantitative Research Titles are as follows:

Business and Economics

“Statistical Analysis of Supply Chain Disruptions on Retail Sales”
“Quantitative Examination of Consumer Loyalty Programs in the Fast Food Industry”
“Predicting Stock Market Trends Using Machine Learning Algorithms”
“Influence of Workplace Environment on Employee Productivity: A Quantitative Study”
“Impact of Economic Policies on Small Businesses: A Regression Analysis”
“Customer Satisfaction and Profit Margins: A Quantitative Correlation Study”
“Analyzing the Role of Marketing in Brand Recognition: A Statistical Overview”
“Quantitative Effects of Corporate Social Responsibility on Consumer Trust”
“Price Elasticity of Demand for Luxury Goods: A Case Study”
“The Relationship Between Fiscal Policy and Inflation Rates: A Time-Series Analysis”
“Factors Influencing E-commerce Conversion Rates: A Quantitative Exploration”
“Examining the Correlation Between Interest Rates and Consumer Spending”
“Standardized Testing and Academic Performance: A Quantitative Evaluation”
“Teaching Strategies and Student Learning Outcomes in Secondary Schools: A Quantitative Study”
“The Relationship Between Extracurricular Activities and Academic Success”
“Influence of Parental Involvement on Children’s Educational Achievements”
“Digital Literacy in Primary Schools: A Quantitative Assessment”
“Learning Outcomes in Blended vs. Traditional Classrooms: A Comparative Analysis”
“Correlation Between Teacher Experience and Student Success Rates”
“Analyzing the Impact of Classroom Technology on Reading Comprehension”
“Gender Differences in STEM Fields: A Quantitative Analysis of Enrollment Data”
“The Relationship Between Homework Load and Academic Burnout”
“Assessment of Special Education Programs in Public Schools”
“Role of Peer Tutoring in Improving Academic Performance: A Quantitative Study”

Medicine and Health Sciences

“The Impact of Sleep Duration on Cardiovascular Health: A Cross-sectional Study”
“Analyzing the Efficacy of Various Antidepressants: A Meta-Analysis”
“Patient Satisfaction in Telehealth Services: A Quantitative Assessment”
“Dietary Habits and Incidence of Heart Disease: A Quantitative Review”
“Correlations Between Stress Levels and Immune System Functioning”
“Smoking and Lung Function: A Quantitative Analysis”
“Influence of Physical Activity on Mental Health in Older Adults”
“Antibiotic Resistance Patterns in Community Hospitals: A Quantitative Study”
“The Efficacy of Vaccination Programs in Controlling Disease Spread: A Time-Series Analysis”
“Role of Social Determinants in Health Outcomes: A Quantitative Exploration”
“Impact of Hospital Design on Patient Recovery Rates”
“Quantitative Analysis of Dietary Choices and Obesity Rates in Children”

Social Sciences

“Examining Social Inequality through Wage Distribution: A Quantitative Study”
“Impact of Parental Divorce on Child Development: A Longitudinal Study”
“Social Media and its Effect on Political Polarization: A Quantitative Analysis”
“The Relationship Between Religion and Social Attitudes: A Statistical Overview”
“Influence of Socioeconomic Status on Educational Achievement”
“Quantifying the Effects of Community Programs on Crime Reduction”
“Public Opinion and Immigration Policies: A Quantitative Exploration”
“Analyzing the Gender Representation in Political Offices: A Quantitative Study”
“Impact of Mass Media on Public Opinion: A Regression Analysis”
“Influence of Urban Design on Social Interactions in Communities”
“The Role of Social Support in Mental Health Outcomes: A Quantitative Analysis”
“Examining the Relationship Between Substance Abuse and Employment Status”

Engineering and Technology

“Performance Evaluation of Different Machine Learning Algorithms in Autonomous Vehicles”
“Material Science: A Quantitative Analysis of Stress-Strain Properties in Various Alloys”
“Impacts of Data Center Cooling Solutions on Energy Consumption”
“Analyzing the Reliability of Renewable Energy Sources in Grid Management”
“Optimization of 5G Network Performance: A Quantitative Assessment”
“Quantifying the Effects of Aerodynamics on Fuel Efficiency in Commercial Airplanes”
“The Relationship Between Software Complexity and Bug Frequency”
“Machine Learning in Predictive Maintenance: A Quantitative Analysis”
“Wearable Technologies and their Impact on Healthcare Monitoring”
“Quantitative Assessment of Cybersecurity Measures in Financial Institutions”
“Analysis of Noise Pollution from Urban Transportation Systems”
“The Influence of Architectural Design on Energy Efficiency in Buildings”

Quantitative Research Topics

Quantitative Research Topics are as follows:

The effects of social media on self-esteem among teenagers.
A comparative study of academic achievement among students of single-sex and co-educational schools.
The impact of gender on leadership styles in the workplace.
The correlation between parental involvement and academic performance of students.
The effect of mindfulness meditation on stress levels in college students.
The relationship between employee motivation and job satisfaction.
The effectiveness of online learning compared to traditional classroom learning.
The correlation between sleep duration and academic performance among college students.
The impact of exercise on mental health among adults.
The relationship between social support and psychological well-being among cancer patients.
The effect of caffeine consumption on sleep quality.
A comparative study of the effectiveness of cognitive-behavioral therapy and pharmacotherapy in treating depression.
The relationship between physical attractiveness and job opportunities.
The correlation between smartphone addiction and academic performance among high school students.
The impact of music on memory recall among adults.
The effectiveness of parental control software in limiting children’s online activity.
The relationship between social media use and body image dissatisfaction among young adults.
The correlation between academic achievement and parental involvement among minority students.
The impact of early childhood education on academic performance in later years.
The effectiveness of employee training and development programs in improving organizational performance.
The relationship between socioeconomic status and access to healthcare services.
The correlation between social support and academic achievement among college students.
The impact of technology on communication skills among children.
The effectiveness of mindfulness-based stress reduction programs in reducing symptoms of anxiety and depression.
The relationship between employee turnover and organizational culture.
The correlation between job satisfaction and employee engagement.
The impact of video game violence on aggressive behavior among children.
The effectiveness of nutritional education in promoting healthy eating habits among adolescents.
The relationship between bullying and academic performance among middle school students.
The correlation between teacher expectations and student achievement.
The impact of gender stereotypes on career choices among high school students.
The effectiveness of anger management programs in reducing violent behavior.
The relationship between social support and recovery from substance abuse.
The correlation between parent-child communication and adolescent drug use.
The impact of technology on family relationships.
The effectiveness of smoking cessation programs in promoting long-term abstinence.
The relationship between personality traits and academic achievement.
The correlation between stress and job performance among healthcare professionals.
The impact of online privacy concerns on social media use.
The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
The relationship between teacher feedback and student motivation.
The correlation between physical activity and academic performance among elementary school students.
The impact of parental divorce on academic achievement among children.
The effectiveness of diversity training in improving workplace relationships.
The relationship between childhood trauma and adult mental health.
The correlation between parental involvement and substance abuse among adolescents.
The impact of social media use on romantic relationships among young adults.
The effectiveness of assertiveness training in improving communication skills.
The relationship between parental expectations and academic achievement among high school students.
The correlation between sleep quality and mood among adults.
The impact of video game addiction on academic performance among college students.
The effectiveness of group therapy in treating eating disorders.
The relationship between job stress and job performance among teachers.
The correlation between mindfulness and emotional regulation.
The impact of social media use on self-esteem among college students.
The effectiveness of parent-teacher communication in promoting academic achievement among elementary school students.
The impact of renewable energy policies on carbon emissions
The relationship between employee motivation and job performance
The effectiveness of psychotherapy in treating eating disorders
The correlation between physical activity and cognitive function in older adults
The effect of childhood poverty on adult health outcomes
The impact of urbanization on biodiversity conservation
The relationship between work-life balance and employee job satisfaction
The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating trauma
The correlation between parenting styles and child behavior
The effect of social media on political polarization
The impact of foreign aid on economic development
The relationship between workplace diversity and organizational performance
The effectiveness of dialectical behavior therapy in treating borderline personality disorder
The correlation between childhood abuse and adult mental health outcomes
The effect of sleep deprivation on cognitive function
The impact of trade policies on international trade and economic growth
The relationship between employee engagement and organizational commitment
The effectiveness of cognitive therapy in treating postpartum depression
The correlation between family meals and child obesity rates
The effect of parental involvement in sports on child athletic performance
The impact of social entrepreneurship on sustainable development
The relationship between emotional labor and job burnout
The effectiveness of art therapy in treating dementia
The correlation between social media use and academic procrastination
The effect of poverty on childhood educational attainment
The impact of urban green spaces on mental health
The relationship between job insecurity and employee well-being
The effectiveness of virtual reality exposure therapy in treating anxiety disorders
The correlation between childhood trauma and substance abuse
The effect of screen time on children’s social skills
The impact of trade unions on employee job satisfaction
The relationship between cultural intelligence and cross-cultural communication
The effectiveness of acceptance and commitment therapy in treating chronic pain
The correlation between childhood obesity and adult health outcomes
The effect of gender diversity on corporate performance
The impact of environmental regulations on industry competitiveness.
The impact of renewable energy policies on greenhouse gas emissions
The relationship between workplace diversity and team performance
The effectiveness of group therapy in treating substance abuse
The correlation between parental involvement and social skills in early childhood
The effect of technology use on sleep patterns
The impact of government regulations on small business growth
The relationship between job satisfaction and employee turnover
The effectiveness of virtual reality therapy in treating anxiety disorders
The correlation between parental involvement and academic motivation in adolescents
The effect of social media on political engagement
The impact of urbanization on mental health
The relationship between corporate social responsibility and consumer trust
The correlation between early childhood education and social-emotional development
The effect of screen time on cognitive development in young children
The impact of trade policies on global economic growth
The relationship between workplace diversity and innovation
The effectiveness of family therapy in treating eating disorders
The correlation between parental involvement and college persistence
The effect of social media on body image and self-esteem
The impact of environmental regulations on business competitiveness
The relationship between job autonomy and job satisfaction
The effectiveness of virtual reality therapy in treating phobias
The correlation between parental involvement and academic achievement in college
The effect of social media on sleep quality
The impact of immigration policies on social integration
The relationship between workplace diversity and employee well-being
The effectiveness of psychodynamic therapy in treating personality disorders
The correlation between early childhood education and executive function skills
The effect of parental involvement on STEM education outcomes
The impact of trade policies on domestic employment rates
The relationship between job insecurity and mental health
The effectiveness of exposure therapy in treating PTSD
The correlation between parental involvement and social mobility
The effect of social media on intergroup relations
The impact of urbanization on air pollution and respiratory health.
The relationship between emotional intelligence and leadership effectiveness
The effectiveness of cognitive-behavioral therapy in treating depression
The correlation between early childhood education and language development
The effect of parental involvement on academic achievement in STEM fields
The impact of trade policies on income inequality
The relationship between workplace diversity and customer satisfaction
The effectiveness of mindfulness-based therapy in treating anxiety disorders
The correlation between parental involvement and civic engagement in adolescents
The effect of social media on mental health among teenagers
The impact of public transportation policies on traffic congestion
The relationship between job stress and job performance
The effectiveness of group therapy in treating depression
The correlation between early childhood education and cognitive development
The effect of parental involvement on academic motivation in college
The impact of environmental regulations on energy consumption
The relationship between workplace diversity and employee engagement
The effectiveness of art therapy in treating PTSD
The correlation between parental involvement and academic success in vocational education
The effect of social media on academic achievement in college
The impact of tax policies on economic growth
The relationship between job flexibility and work-life balance
The effectiveness of acceptance and commitment therapy in treating anxiety disorders
The correlation between early childhood education and social competence
The effect of parental involvement on career readiness in high school
The impact of immigration policies on crime rates
The relationship between workplace diversity and employee retention
The effectiveness of play therapy in treating trauma
The correlation between parental involvement and academic success in online learning
The effect of social media on body dissatisfaction among women
The impact of urbanization on public health infrastructure
The relationship between job satisfaction and job performance
The effectiveness of eye movement desensitization and reprocessing therapy in treating PTSD
The correlation between early childhood education and social skills in adolescence
The effect of parental involvement on academic achievement in the arts
The impact of trade policies on foreign investment
The relationship between workplace diversity and decision-making
The effectiveness of exposure and response prevention therapy in treating OCD
The correlation between parental involvement and academic success in special education
The impact of zoning laws on affordable housing
The relationship between job design and employee motivation
The effectiveness of cognitive rehabilitation therapy in treating traumatic brain injury
The correlation between early childhood education and social-emotional learning
The effect of parental involvement on academic achievement in foreign language learning
The impact of trade policies on the environment
The relationship between workplace diversity and creativity
The effectiveness of emotion-focused therapy in treating relationship problems
The correlation between parental involvement and academic success in music education
The effect of social media on interpersonal communication skills
The impact of public health campaigns on health behaviors
The relationship between job resources and job stress
The effectiveness of equine therapy in treating substance abuse
The correlation between early childhood education and self-regulation
The effect of parental involvement on academic achievement in physical education
The impact of immigration policies on cultural assimilation
The relationship between workplace diversity and conflict resolution
The effectiveness of schema therapy in treating personality disorders
The correlation between parental involvement and academic success in career and technical education
The effect of social media on trust in government institutions
The impact of urbanization on public transportation systems
The relationship between job demands and job stress
The correlation between early childhood education and executive functioning
The effect of parental involvement on academic achievement in computer science
The effectiveness of cognitive processing therapy in treating PTSD
The correlation between parental involvement and academic success in homeschooling
The effect of social media on cyberbullying behavior
The impact of urbanization on air quality
The effectiveness of dance therapy in treating anxiety disorders
The correlation between early childhood education and math achievement
The effect of parental involvement on academic achievement in health education
The impact of global warming on agriculture
The effectiveness of narrative therapy in treating depression
The correlation between parental involvement and academic success in character education
The effect of social media on political participation
The impact of technology on job displacement
The relationship between job resources and job satisfaction
The effectiveness of art therapy in treating addiction
The correlation between early childhood education and reading comprehension
The effect of parental involvement on academic achievement in environmental education
The impact of income inequality on social mobility
The relationship between workplace diversity and organizational culture
The effectiveness of solution-focused brief therapy in treating anxiety disorders
The correlation between parental involvement and academic success in physical therapy education
The effect of social media on misinformation
The impact of green energy policies on economic growth
The relationship between job demands and employee well-being
The correlation between early childhood education and science achievement
The effect of parental involvement on academic achievement in religious education
The impact of gender diversity on corporate governance
The relationship between workplace diversity and ethical decision-making
The correlation between parental involvement and academic success in dental hygiene education
The effect of social media on self-esteem among adolescents
The impact of renewable energy policies on energy security
The effect of parental involvement on academic achievement in social studies
The impact of trade policies on job growth
The relationship between workplace diversity and leadership styles
The correlation between parental involvement and academic success in online vocational training
The effect of social media on self-esteem among men
The impact of urbanization on air pollution levels
The effectiveness of music therapy in treating depression
The correlation between early childhood education and math skills
The effect of parental involvement on academic achievement in language arts
The impact of immigration policies on labor market outcomes
The effectiveness of hypnotherapy in treating phobias
The effect of social media on political engagement among young adults
The impact of urbanization on access to green spaces
The relationship between job crafting and job satisfaction
The effectiveness of exposure therapy in treating specific phobias
The correlation between early childhood education and spatial reasoning
The effect of parental involvement on academic achievement in business education
The impact of trade policies on economic inequality
The effectiveness of narrative therapy in treating PTSD
The correlation between parental involvement and academic success in nursing education
The effect of social media on sleep quality among adolescents
The impact of urbanization on crime rates
The relationship between job insecurity and turnover intentions
The effectiveness of pet therapy in treating anxiety disorders
The correlation between early childhood education and STEM skills
The effect of parental involvement on academic achievement in culinary education
The impact of immigration policies on housing affordability
The relationship between workplace diversity and employee satisfaction
The effectiveness of mindfulness-based stress reduction in treating chronic pain
The correlation between parental involvement and academic success in art education
The effect of social media on academic procrastination among college students
The impact of urbanization on public safety services.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

200+ Funny Research Topics

500+ Sports Research Topics

300+ American History Research Paper Topics

500+ Cyber Security Research Topics

500+ Environmental Research Topics

500+ Economics Research Topics

Yearly paid plans are up to 65% off for the spring sale. Limited time only! 🌸

Form Builder
Survey Maker
AI Form Generator
AI Survey Tool
AI Quiz Maker
Store Builder
WordPress Plugin

HubSpot CRM

Google Sheets

Google Analytics

Microsoft Excel

Popular Forms
Job Application Form Template
Rental Application Form Template
Hotel Accommodation Form Template
Online Registration Form Template
Employment Application Form Template
Application Forms
Booking Forms
Consent Forms
Contact Forms
Donation Forms
Customer Satisfaction Surveys
Employee Satisfaction Surveys
Evaluation Surveys
Feedback Surveys
Market Research Surveys
Personality Quiz Template
Geography Quiz Template
Math Quiz Template
Science Quiz Template
Vocabulary Quiz Template

Try without registration Quick Start

Read engaging stories, how-to guides, learn about forms.app features.

Inspirational ready-to-use templates for getting started fast and powerful.

Spot-on guides on how to use forms.app and make the most out of it.

See the technical measures we take and learn how we keep your data safe and secure.

Integrations
Help Center
Sign In Sign Up Free
What is non-experimental research: Definition, types & examples

What is non-experimental research: Definition, types & examples

Defne Çobanoğlu

The experimentation method is very useful for getting information on a specific subject. However, when experimenting is not possible or practical, there is another way of collecting data for those interested. It's a non-experimental way, to say the least.

In this article, we have gathered information on non-experimental research, clearly defined what it is and when one should use it, and listed the types of non-experimental research. We also gave some useful examples to paint a better picture. Let us get started.

What is non-experimental research?

Non-experimental research is a type of research design that is based on observation and measuring instead of experimentation with randomly assigned participants.

What characterizes this research design is the fact that it lacks the manipulation of independent variables . Because of this fact, the non-experimental research is based on naturally occurring conditions, and there is no involvement of external interventions. Therefore, the researchers doing this method must not rely heavily on interviews, surveys , or case studies.

When to use non-experimental research?

An experiment is done when a researcher is investigating the relationship between one or two phenomena and has a theory or hypothesis on the relationship between two variables that are involved. The researcher can carry out an experiment when it is ethical, possible, and feasible to do one.

However, when an experiment can not be done because of a limitation, then they decide to opt for a non-experimental research design . Non-experimental research is considered preferable in some conditions, including:

When the manipulation of the independent variable is not possible because of ethical or practical concerns
When the subjects of an experimental design can not be randomly assigned to treatments.
When the research question is too extensive or it relates to a general experience.
When researchers want to do a starter research before investing in more extensive research.
When the research question is about the statistical relationship between variables , but in a noncausal context.
Characteristics of non-experimental research

Non-experimental research has some characteristics that clearly define the framework of this research method. They provide a clear distinction between experimental design and non-experimental design. Let us see some of them:

Non-experimental research does not involve the manipulation of variables .
The aim of this research type is to explore the factors as they naturally occur .
This method is used when experimentation is not possible because of ethical or practical reasons .
Instead of creating a sample or participant group, the existing groups or natural thresholds are used during the research.
This research method is not about finding causality between two variables.
Most studies are done on past events or historical occurrences to make sense of specific research questions.
Types of non-experimental research

Non-experimental research types

What makes research non-experimental research is the fact that the researcher does not manipulate the factors, does not randomly assign the participants, and observes the existing groups. But this research method can also be divided into different types. These types are:

Correlational research:

In correlation studies, the researcher does not manipulate the variables and is not interested in controlling the extraneous variables. They only observe and assess the relationship between them. For example, a researcher examines students’ study hours every day and their overall academic performance. The positive correlation this between study hours and academic performance suggests a statistical association.

Quasi-experimental research:

In quasi-experimental research, the researcher does not randomly assign the participants into two groups. Because you can not deliberately deprive someone of treatment, the researcher uses natural thresholds or dividing points . For example, examining students from two different high schools with different education methods.

Cross-sectional research:

In cross-sectional research, the researcher studies and compares a portion of a population at the same time . It does not involve random assignment or any outside manipulation. For example, a study on smokers and non-smokers in a specific area.

Observational research:

In observational research, the researcher once again does not manipulate any aspect of the study, and their main focus is observation of the participants . For example, a researcher examining a group of children playing in a playground would be a good example.

Non-experimental research examples

Non-experimental research is a good way of collecting information and exploring relationships between variables. It can be used in numerous fields, from social sciences, economics, psychology, education, and market research. When gathering information using secondary research is not enough and an experiment can not be done, this method can bring out new information.

Non-experimental research example #1

Imagine a researcher who wants to see the connection between mobile phone usage before bedtime and the amount of sleep adults get in a night . They can gather a group of individuals to observe and present them with some questions asking about the details of their day, frequency and duration of phone usage, quality of sleep, etc . And observe them by analyzing the findings.

Non-experimental research example #2

Imagine a researcher who wants to explore the correlation between job satisfaction levels among employees and what are the factors that affect this . The researcher can gather all the information they get about the employees’ ages, sexes, positions in the company, working patterns, demographic information, etc .

The research provides the researcher with all the information to make an analysis to identify correlations and patterns. Then, it is possible for researchers and administrators to make informed predictions.

Frequently asked questions about non-experimental research

When not to use non-experimental research?

There are some situations where non-experimental research is not suitable or the best choice. For example, the aim of non-experimental research is not about finding causality therefore, if the researcher wants to explore the relationship between two variables, then this method is not for them. Also, if the control over the variables is extremely important to the test of a theory, then experimentation is a more appropriate option.

What is the difference between experimental and non-experimental research?

Experimental research is an example of primary research where the researcher takes control of all the variables, randomly assigns the participants into different groups, and studies them in a pre-determined environment to test a hypothesis.

On the contrary, non-experimental research does not intervene in any way and only observes and studies the participants in their natural environments to make sense of a phenomenon

What makes a quasi-experiment a non-experiment?

The same as true experimentation, quasi-experiment research also aims to explore a cause-and-effect relationship between independent and dependent variables. However, in quasi-experimental research, the participants are not randomly selected. They are assigned to groups based on non-random criteria .

Is a survey a non-experimental study?

Yes, as the main purpose of a survey or questionnaire is to collect information from participants without outside interference, it makes the survey a non-experimental study. Surveys are used by researchers when experimentation is not possible because of ethical reasons, but first-hand data is needed

What is non-experimental data?

Non-experimental data is data collected by researchers via using non-experimental methods such as observations, interpretation, and interactions. Non-experimental data could both be qualitative or quantitative, depending on the situation.

Advantages of non-experimental research

Non-experimental research has its positive sides that a researcher should have in mind when going through a study. They can start their research by going through the advantages. These advantages are:

It is used to observe and analyze past events .
This method is more affordable than a true experiment .
As the researcher can adapt the methods during the study, this research type is more flexible than an experimental study.
This method allows the researchers to answer specific questions .

Disadvantages of non-experimental research

Even though non-experimental research has its advantages, it also has some disadvantages a researcher should be mindful of. Here are some of them:

The findings of non-experimental research can not be generalized to the whole population. Therefore, it has low external validity .
This research is used to explore only a single variable .
Non-experimental research designs are prone to researcher bias and may not produce neutral results.
Final words

A non-experimental study differs from an experimental study in that there is no intervention or change of internal or extraneous elements. It is a smart way to collect information without the limitations of experimentation. These limitations could be about ethical or practical problems. When you can not do proper experimentation, your other option is to study existing conditions and groups to draw conclusions. This is a non-experimental design .

In this article, we have gathered information on non-experimental research to shed light on the details of this research method. If you are thinking of doing a study, make sure to have this information in mind. And lastly, do not forget to visit our articles on other research methods and so much more!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

Form Features
Data Collection

65+ Parent-teacher conference survey questions (& free templates)

What is judgmental sampling: Definition & examples

16 Best Quizlet alternatives in 2024 (free & paid)

Experimental Vs Non-Experimental Research: 15 Key Differences

There is a general misconception around research that once the research is non-experimental, then it is non-scientific, making it more important to understand what experimental and experimental research entails. Experimental research is the most common type of research, which a lot of people refer to as scientific research.

Non experimental research, on the other hand, is easily used to classify research that is not experimental. It clearly differs from experimental research, and as such has different use cases.

In this article, we will be explaining these differences in detail so as to ensure proper identification during the research process.

What is Experimental Research?

Experimental research is the type of research that uses a scientific approach towards manipulating one or more control variables of the research subject(s) and measuring the effect of this manipulation on the subject. It is known for the fact that it allows the manipulation of control variables.

This research method is widely used in various physical and social science fields, even though it may be quite difficult to execute. Within the information field, they are much more common in information systems research than in library and information management research.

Experimental research is usually undertaken when the goal of the research is to trace cause-and-effect relationships between defined variables. However, the type of experimental research chosen has a significant influence on the results of the experiment.

Therefore bringing us to the different types of experimental research. There are 3 main types of experimental research, namely; pre-experimental, quasi-experimental, and true experimental research.

Pre-experimental Research

Pre-experimental research is the simplest form of research, and is carried out by observing a group or groups of dependent variables after the treatment of an independent variable which is presumed to cause change on the group(s). It is further divided into three types.

One-shot case study research
One-group pretest-posttest research
Static-group comparison

Quasi-experimental Research

The Quasi type of experimental research is similar to true experimental research, but uses carefully selected rather than randomized subjects. The following are examples of quasi-experimental research:

Time series
No equivalent control group design
Counterbalanced design.

True Experimental Research

True experimental research is the most accurate type, and may simply be called experimental research. It manipulates a control group towards a group of randomly selected subjects and records the effect of this manipulation.

True experimental research can be further classified into the following groups:

The posttest-only control group
The pretest-posttest control group
Solomon four-group

Pros of True Experimental Research

Researchers can have control over variables.
It can be combined with other research methods.
The research process is usually well structured.
It provides specific conclusions.
The results of experimental research can be easily duplicated.

Cons of True Experimental Research

It is highly prone to human error.
Exerting control over extraneous variables may lead to the personal bias of the researcher.
It is time-consuming.
It is expensive.
Manipulating control variables may have ethical implications.
It produces artificial results.

What is Non-Experimental Research?

Non-experimental research is the type of research that does not involve the manipulation of control or independent variable. In non-experimental research, researchers measure variables as they naturally occur without any further manipulation.

This type of research is used when the researcher has no specific research question about a causal relationship between 2 different variables, and manipulation of the independent variable is impossible. They are also used when:

subjects cannot be randomly assigned to conditions.
the research subject is about a causal relationship but the independent variable cannot be manipulated.
the research is broad and exploratory
the research pertains to a non-causal relationship between variables.
limited information can be accessed about the research subject.

There are 3 main types of non-experimental research , namely; cross-sectional research, correlation research, and observational research.

Cross-sectional Research

Cross-sectional research involves the comparison of two or more pre-existing groups of people under the same criteria. This approach is classified as non-experimental because the groups are not randomly selected and the independent variable is not manipulated.

For example, an academic institution may want to reward its first-class students with a scholarship for their academic excellence. Therefore, each faculty places students in the eligible and ineligible group according to their class of degree.

In this case, the student’s class of degree cannot be manipulated to qualify him or her for a scholarship because it is an unethical thing to do. Therefore, the placement is cross-sectional.

Correlational Research

Correlational type of research compares the statistical relationship between two variables .Correlational research is classified as non-experimental because it does not manipulate the independent variables.

For example, a researcher may wish to investigate the relationship between the class of family students come from and their grades in school. A questionnaire may be given to students to know the average income of their family, then compare it with CGPAs.

The researcher will discover whether these two factors are positively correlated, negatively corrected, or have zero correlation at the end of the research.

Observational Research

Observational research focuses on observing the behavior of a research subject in a natural or laboratory setting. It is classified as non-experimental because it does not involve the manipulation of independent variables.

A good example of observational research is an investigation of the crowd effect or psychology in a particular group of people. Imagine a situation where there are 2 ATMs at a place, and only one of the ATMs is filled with a queue, while the other is abandoned.

The crowd effect infers that the majority of newcomers will also abandon the other ATM.

You will notice that each of these non-experimental research is descriptive in nature. It then suffices to say that descriptive research is an example of non-experimental research.

Pros of Observational Research

The research process is very close to a real-life situation.
It does not allow for the manipulation of variables due to ethical reasons.
Human characteristics are not subject to experimental manipulation.

Cons of Observational Research

The groups may be dissimilar and nonhomogeneous because they are not randomly selected, affecting the authenticity and generalizability of the study results.
The results obtained cannot be absolutely clear and error-free.

What Are The Differences Between Experimental and Non-Experimental Research?

Definitions

Experimental research is the type of research that uses a scientific approach towards manipulating one or more control variables and measuring their defect on the dependent variables, while non-experimental research is the type of research that does not involve the manipulation of control variables.

The main distinction in these 2 types of research is their attitude towards the manipulation of control variables. Experimental allows for the manipulation of control variables while non-experimental research doesn’t.

Examples of experimental research are laboratory experiments that involve mixing different chemical elements together to see the effect of one element on the other while non-experimental research examples are investigations into the characteristics of different chemical elements.

Consider a researcher carrying out a laboratory test to determine the effect of adding Nitrogen gas to Hydrogen gas. It may be discovered that using the Haber process, one can create Nitrogen gas.

Non-experimental research may further be carried out on Ammonia, to determine its characteristics, behaviour, and nature.

There are 3 types of experimental research, namely; experimental research, quasi-experimental research, and true experimental research. Although also 3 in number, non-experimental research can be classified into cross-sectional research, correlational research, and observational research.

The different types of experimental research are further divided into different parts, while non-experimental research types are not further divided. Clearly, these divisions are not the same in experimental and non-experimental research.

Characteristics

Experimental research is usually quantitative, controlled, and multivariable. Non-experimental research can be both quantitative and qualitative , has an uncontrolled variable, and also a cross-sectional research problem.

The characteristics of experimental research are the direct opposite of that of non-experimental research. The most distinct characteristic element is the ability to control or manipulate independent variables in experimental research and not in non-experimental research.

In experimental research, a level of control is usually exerted on extraneous variables, therefore tampering with the natural research setting. Experimental research settings are usually more natural with no tampering with the extraneous variables.

Data Collection/Tools

The data used during experimental research is collected through observational study, simulations, and surveys while non-experimental data is collected through observations, surveys, and case studies. The main distinction between these data collection tools is case studies and simulations.

Even at that, similar tools are used differently. For example, an observational study may be used during a laboratory experiment that tests how the effect of a control variable manifests over a period of time in experimental research.

However, when used in non-experimental research, data is collected based on the researcher’s discretion and not through a clear scientific reaction. In this case, we see a difference in the level of objectivity.

The goal of experimental research is to measure the causes and effects of variables present in research, while non-experimental research provides very little to no information about causal agents.

Experimental research answers the question of why something is happening. This is quite different in non-experimental research, as they are more descriptive in nature with the end goal being to describe what .

Experimental research is mostly used to make scientific innovations and find major solutions to problems while non-experimental research is used to define subject characteristics, measure data trends, compare situations and validate existing conditions.

For example, if experimental research results in an innovative discovery or solution, non-experimental research will be conducted to validate this discovery. This research is done for a period of time in order to properly study the subject of research.

Experimental research process is usually well structured and as such produces results with very little to no errors, while non-experimental research helps to create real-life related experiments. There are a lot more advantages of experimental and non-experimental research , with the absence of each of these advantages in the other leaving it at a disadvantage.

For example, the lack of a random selection process in non-experimental research leads to the inability to arrive at a generalizable result. Similarly, the ability to manipulate control variables in experimental research may lead to the personal bias of the researcher.

Disadvantage

Experimental research is highly prone to human error while the major disadvantage of non-experimental research is that the results obtained cannot be absolutely clear and error-free. In the long run, the error obtained due to human error may affect the results of the experimental research.

Some other disadvantages of experimental research include the following; extraneous variables cannot always be controlled, human responses can be difficult to measure, and participants may also cause bias.

In experimental research, researchers can control and manipulate control variables, while in non-experimental research, researchers cannot manipulate these variables. This cannot be done due to ethical reasons.

For example, when promoting employees due to how well they did in their annual performance review, it will be unethical to manipulate the results of the performance review (independent variable). That way, we can get impartial results of those who deserve a promotion and those who don’t.

Experimental researchers may also decide to eliminate extraneous variables so as to have enough control over the research process. Once again, this is something that cannot be done in non-experimental research because it relates more to real-life situations.

Experimental research is carried out in an unnatural setting because most of the factors that influence the setting are controlled while the non-experimental research setting remains natural and uncontrolled. One of the things usually tampered with during research is extraneous variables.

In a bid to get a perfect and well-structured research process and results, researchers sometimes eliminate extraneous variables. Although sometimes seen as insignificant, the elimination of these variables may affect the research results.

Consider the optimization problem whose aim is to minimize the cost of production of a car, with the constraints being the number of workers and the number of hours they spend working per day.

In this problem, extraneous variables like machine failure rates or accidents are eliminated. In the long run, these things may occur and may invalidate the result.

Cause-Effect Relationship

The relationship between cause and effect is established in experimental research while it cannot be established in non-experimental research. Rather than establish a cause-effect relationship, non-experimental research focuses on providing descriptive results.

Although it acknowledges the causal variable and its effect on the dependent variables, it does not measure how or the extent to which these dependent variables change. It, however, observes these changes, compares the changes in 2 variables, and describes them.

Experimental research does not compare variables while non-experimental research does. It compares 2 variables and describes the relationship between them.

The relationship between these variables can be positively correlated, negatively correlated or not correlated at all. For example, consider a case whereby the subject of research is a drum, and the control or independent variable is the drumstick.

Experimental research will measure the effect of hitting the drumstick on the drum, where the result of this research will be sound. That is, when you hit a drumstick on a drum, it makes a sound.

Non-experimental research, on the other hand, will investigate the correlation between how hard the drum is hit and the loudness of the sound that comes out. That is, if the sound will be higher with a harder bang, lower with a harder bang, or will remain the same no matter how hard we hit the drum.

Quantitativeness

Experimental research is a quantitative research method while non-experimental research can be both quantitative and qualitative depending on the time and the situation where it is been used. An example of a non-experimental quantitative research method is correlational research .

Researchers use it to correlate two or more variables using mathematical analysis methods. The original patterns, relationships, and trends between variables are observed, then the impact of one of these variables on the other is recorded along with how it changes the relationship between the two variables.

Observational research is an example of non-experimental research, which is classified as a qualitative research method.

Cross-section

Experimental research is usually single-sectional while non-experimental research is cross-sectional. That is, when evaluating the research subjects in experimental research, each group is evaluated as an entity.

For example, let us consider a medical research process investigating the prevalence of breast cancer in a certain community. In this community, we will find people of different ages, ethnicities, and social backgrounds.

If a significant amount of women from a particular age are found to be more prone to have the disease, the researcher can conduct further studies to understand the reason behind it. A further study into this will be experimental and the subject won’t be a cross-sectional group.

A lot of researchers consider the distinction between experimental and non-experimental research to be an extremely important one. This is partly due to the fact that experimental research can accommodate the manipulation of independent variables, which is something non-experimental research can not.

Therefore, as a researcher who is interested in using any one of experimental and non-experimental research, it is important to understand the distinction between these two. This helps in deciding which method is better for carrying out particular research.

Connect to Formplus, Get Started Now - It's Free!

examples of experimental research
non experimental research
busayo.longe

Experimental Research Designs: Types, Examples & Methods

Ultimate guide to experimental research. It’s definition, types, characteristics, uses, examples and methodolgy

What is Experimenter Bias? Definition, Types & Mitigation

In this article, we will look into the concept of experimental bias and how it can be identified in your research

Simpson’s Paradox & How to Avoid it in Experimental Research

In this article, we are going to look at Simpson’s Paradox from its historical point and later, we’ll consider its effect in...

Response vs Explanatory Variables: Definition & Examples

In this article, we’ll be comparing the two types of variables, what they both mean and see some of their real-life applications in research

Formplus - For Seamless Data Collection

Collect data the right way with a versatile data collection tool. try formplus and transform your work productivity today..

The Federal Register

The daily journal of the united states government, request access.

Due to aggressive automated scraping of FederalRegister.gov and eCFR.gov, programmatic access to these sites is limited to access to our extensive developer APIs.

If you are human user receiving this message, we can add your IP address to a set of IPs that can access FederalRegister.gov & eCFR.gov; complete the CAPTCHA (bot test) below and click "Request Access". This process will be necessary for each IP address you wish to access the site from, requests are valid for approximately one quarter (three months) after which the process may need to be repeated.

An official website of the United States government.

If you want to request a wider IP range, first request access for your current IP, and then use the "Site Feedback" button found in the lower left-hand side to make the request.

IMAGES

7.1 Overview of Non-Experimental Research
Accounting Nest
😂 Quantitative research title. Format for a quantitative research
Quantitative Research Title
Explain Different Types of Non Experimental Research Design
quantitative research title examples for ict students

VIDEO

QUANTITATIVE RESEARCH
TYPES OF RESEARCH : Quick Review (Comprehensive Exam Reviewer)
QUANTITATIVE RESEARCH TITLE IDEAS RELATED TO MULTITASKING #geniusai #researchideas
Sample Qualitative and Quantitative Research Titles
Intro to Quantitative Research Part 2
Quantitative Research || Experimental Research || Non Experimental Research

COMMENTS

Quantitative Research with Nonexperimental Designs
There are two main types of nonexperimental research designs: comparative design and correlational design. In comparative research, the researcher examines the differences between two or more groups on the phenomenon that is being studied. For example, studying gender difference in learning mathematics is a comparative research.
6.1 Overview of Non-Experimental Research
Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world). Most researchers in psychology consider the distinction between experimental ...
7.1 Overview of Nonexperimental Research
Key Takeaways. Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both. There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables.
Overview of Nonexperimental Research
Key Takeaways. Nonexperimental research is research that lacks the manipulation of an independent variable, control of extraneous variables through random assignment, or both. There are three broad types of nonexperimental research. Single-variable research focuses on a single variable rather than a relationship between variables.
Non-experimental research: advantages & examples
Examples of non-experimental research. Examples of non-experimental research include statistical surveys, which survey public opinion on an issue to determine a common viewpoint. Or surveys, where a set of statistical data is available and these are interpreted and organized to obtain as much relevant data as possible.
6.1: Overview of Non-Experimental Research
Non-experimental research falls into three broad categories: cross-sectional research, correlational research, and observational research. First, cross-sectional research involves comparing two or more pre-existing groups of people. What makes this approach non-experimental is that there is no manipulation of an independent variable and no ...
1.6: Non-Experimental Research
Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world). Most researchers in social sciences consider the distinction between ...
Overview of Non-Experimental Research
Non-experimental research is research that lacks the manipulation of an independent variable. Rather than manipulating an independent variable, researchers conducting non-experimental research simply measure variables as they naturally occur (in the lab or real world). Most researchers in psychology consider the distinction between experimental ...
6.2: Overview of Non-Experimental Research
When to Use Non-Experimental Research. As we saw in the last chapter, experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable.It stands to reason, therefore, that non-experimental research is appropriate—even ...
6: Non-Experimental Research
6.3: Correlational Research. Correlational research is a type of non-experimental research in which the researcher measures two variables and assesses the statistical relationship (i.e., the correlation) between them with little or no effort to control extraneous variables. There are many reasons that researchers interested in statistical ...
PDF and Survey Research Nonexperimental Research Designs
Characteristics of Survey Research In survey research, the researcher selects a sample of respondents and administers a questionnaire or conducts interviews to gather data, which are then used to describe the population Surveys are used to learn about attitudes, beliefs, opinions, behaviors, to name a few
A Primer to Experimental and Nonexperimental Quantitative Research: The
Quantitative research turns information collected about people or about processes into numerical data. Depending on the underlying purpose, the goal is to address questions that have to do with intervention, prognosis, causation, association, description, or assessment. In experimental research, an intervention is manipulated.
Types of Research Designs Compared
Types of Research Designs Compared | Guide & Examples. Published on June 20, 2019 by Shona McCombes.Revised on June 22, 2023. When you start planning a research project, developing research questions and creating a research design, you will have to make various decisions about the type of research you want to do.. There are many ways to categorize different types of research.
Non-experimental research: What it is, Types & Tips
Non-experimental research is the type of research that lacks an independent variable. Instead, the researcher observes the context in which the phenomenon occurs and analyzes it to obtain information. Unlike experimental research, where the variables are held constant, non-experimental research happens during the study when the researcher ...
2.5: Experimental and Non-experimental Research
Non-experimental research. Non-experimental research is a broad term that covers "any study in which the researcher doesn't have quite as much control as they do in an experiment". Obviously, control is something that scientists like to have, but as the previous example illustrates, there are lots of situations in which you can't or ...
Non-Experimental Research Methods in Quantitative Research
The first type is known as descriptive non-experimental research method, in which the fundamental concern for the researcher lies in describing some phenomena of interest or documenting its characteristics (Belli, n.d.). This typology is mainly used to document the status quo of a phenomenon under investigation or to perform a needs assessment ...
Research Study Designs: Non-experimental
quasi-experimental, and non-experimental). Examples of the most common non-experimental designs are listed in Table 1. Although, in general, this category has the lowest level of scientific rigor, each design within this category varies as to its own individual level of scientific validity. Commonly, non-experimental studies are purely obser-
500+ Quantitative Research Titles and Topics
Quantitative Research Topics. Quantitative Research Topics are as follows: The effects of social media on self-esteem among teenagers. A comparative study of academic achievement among students of single-sex and co-educational schools. The impact of gender on leadership styles in the workplace.
Quantitative Research Designs: Non-Experimental vs. Experimental
Without this level of control, you cannot determine any causal effects. While validity is still a concern in non-experimental research, the concerns are more about the validity of the measurements, rather than the validity of the effects. Finally, a quasi-experimental design is a combination of the two designs described above.
What is non-experimental research: Definition, types & examples
Non-experimental research is a type of research design that is based on observation and measuring instead of experimentation with randomly assigned participants. What characterizes this research design is the fact that it lacks the manipulation of independent variables. Because of this fact, the non-experimental research is based on naturally ...
(PDF) Nonexperimental Quantitative Research and Its Role in Guiding
Cook and Cook (2008) argue that a correlational research design is ideal for this study because it addresses the non-experimental quantitative descriptive and correlational surveys. In addition ...
PDF Quantitative Research Designs: Experimental, Quasi-Experimental, and
A placebo is an intervention with no effect, such as a dummy pill. Standard or usual health care. In nursing studies, for example, patients in the control group typically receive "usual care" because no care would be unethical. A lower dose of treatment or an alternative treatment.
Experimental Vs Non-Experimental Research: 15 Key Differences
An example of a non-experimental quantitative research method is correlational research. Researchers use it to correlate two or more variables using mathematical analysis methods. The original patterns, relationships, and trends between variables are observed, then the impact of one of these variables on the other is recorded along with how it ...
PDF NIGMS U-RISE/MARC Training Grants (T34) PAR-24-137) (PAR-24-138)
NIH provides funds to help defray other research training expenses, such as health insurance, staff salaries, consultant costs, equipment, research supplies, and faculty/staff travel directly related to the research training program. MARC TRE: $10,000/trainee/year (maximum $320,000/year). U-RISE TRE: $12,500/trainee/year (maximum $400,000/year).
Highly Sensitive Qualitative and Quantitative Identification of ...
The amplitude and frequency shift changes of the terahertz transmission spectra caused by the different refractive indices of cashmere/wool can achieve highly sensitive label−free qualitative and quantitative identification of both. The experimental results show that the terahertz metasurface biosensor can work at a concentration of 0.02 mg/mL.
Federal Register :: New Source Performance Standards for Greenhouse Gas
For example, the half degree of warming from 1.5 to 2 °C (0.9 °F of warming from 2.7 °F to 3.6 °F) above preindustrial temperatures is projected on a global scale to expose 420 million more people to frequent extreme heatwaves at least every five years, and 62 million more people to frequent exceptional heatwaves at least every five years ...

6.1 Overview of Non-Experimental Research

What Is Non-Experimental Research?

When to Use Non-Experimental Research

Types of Non-Experimental Research

Internal Validity Revisited

Key Takeaways

Share This Book

7.1 Overview of Nonexperimental Research

What Is Nonexperimental Research?

When to Use Nonexperimental Research

Types of Nonexperimental Research

Internal Validity Revisited

Key Takeaways

Overview of Nonexperimental Research

What Is Nonexperimental Research?

When to Use Nonexperimental Research

Types of Nonexperimental Research

Internal Validity Revisited

Share This Book

Non-experimental research: what is it, features, advantages and examples?

What is non-experimental research?

Characteristics of non-experimental research

When is non-experimental research used?

Advantages and disadvantages of non-experimental research

Types of non-experimental research

Examples of non-experimental research

1:1 live online presentation: QUESTIONPRO MARKET RESEARCH SOFTWARE

Try software for market research and experience management now for 10 days free of charge!

SHARE THIS ARTICLE

FURTHER INFORMATION

PRESS RELEASES

28 Overview of Non-Experimental Research

What Is Non-Experimental Research?

When to Use Non-Experimental Research

Types of Non-Experimental Research

Cross-Sectional, Longitudinal, and Cross-Sequential Studies

Internal Validity Revisited

Share This Book

6: Non-Experimental Research

Non-experimental research: What it is, overview & advantages

Characteristics of non-experimental research

Types of non-experimental research

When to use non-experimental research

Advantages and disadvantages

Difference between experimental and non-experimental research

MORE LIKE THIS

The Best Email Survey Tool to Boost Your Feedback Game

Top 10 Employee Engagement Survey Tools

Top 20 Employee Engagement Software Solutions

15 Best Customer Experience Software of 2024

Other categories

2.5: Experimental and Non-experimental Research

Experimental research

Non-experimental research

Non-Experimental Research Methods in Quantitative Research Report (Assessment)

Reference List

500+ Quantitative Research Titles and Topics

Quantitative Research Titles

Business and Economics

Medicine and Health Sciences

Social Sciences

Engineering and Technology

Quantitative Research Topics

About the author

Muhammad Hassan

You may also like

200+ Funny Research Topics

500+ Sports Research Topics

300+ American History Research Paper Topics

500+ Cyber Security Research Topics

500+ Environmental Research Topics

500+ Economics Research Topics

Correlational research:

Quasi-experimental research:

Cross-sectional research:

Observational research:

Non-experimental research example #1

Non-experimental research example #2

When not to use non-experimental research?

What is the difference between experimental and non-experimental research?