discuss the strengths of quantitative research essay

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

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Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

• Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
• Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
• Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
• You can summarize vast sources of information and make comparisons across categories and over time; and,
• Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

• Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
• Uses a static and rigid approach and so employs an inflexible process of discovery;
• The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
• Results provide less detail on behavior, attitudes, and motivation;
• Researcher may collect a much narrower and sometimes superficial dataset;
• Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
• The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
• Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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What Is Quantitative Research? | Definition & Methods

Published on 4 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analysing non-numerical data (e.g. text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

• What is the demographic makeup of Singapore in 2020?
• How has the average temperature changed globally over the last century?
• Does environmental pollution affect the prevalence of honey bees?
• Does working from home increase productivity for people with long commutes?

Table of contents

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

• In descriptive research , you simply seek an overall summary of your study variables.
• In correlational research , you investigate relationships between your study variables.
• In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalised to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

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Once data is collected, you may need to process it before it can be analysed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualise your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalisations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardise data collection and generalise findings . Strengths of this approach include:

• Replication

Repeating the study is possible because of standardised data collection protocols and tangible definitions of abstract concepts.

• Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

• Large samples

Data from large samples can be processed and analysed using reliable and consistent procedures through quantitative data analysis.

• Hypothesis testing

Using formalised and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

• Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

• Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

• Structural bias

Despite standardised procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

• Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Quantitative Research Essay Examples

A quantitative research essay analyzes numerical data in the form of trends, opinions, or efficiency results. This academic writing genre requires you to generalize the figures across a broad group of people and make a relevant conclusion. The possible research methods comprise questionnaires, polls, and surveys, but the results shall be processed with computational techniques and statistics.

For instance, a paper on organized crime in Texas will calculate the number of offenses committed over a given period and compare the findings with the same period in the past.

Below we’ve gathered dozens of quantitative essay examples to help you brainstorm ideas. You will surely find here a couple of papers that meet your needs.

57 Best Quantitative Research Essay Examples

Audit report for the university of alabama system.

• Subjects: Economics Financial Reporting

Decision Making: Starbucks Transformational Experience

• Subjects: Business Case Study
• Words: 2003

Business Problem Matrix and Research Question Hypotheses

• Subjects: Sciences Statistics
• Words: 2058

Asians Seeking U.S. Education

• Subjects: Education Education Theories
• Words: 3014

Facial Feedback Hypothesis

• Subjects: Psychological Principles Psychology
• Words: 2206

User Satisfaction and Service Quality in Academic Libraries: Use of LibQUAL+

• Subjects: Education Education System
• Words: 4019

Demography of Harbor Hills, Austin, TX

• Subjects: Sociological Theories Sociology
• Words: 2050

Predicting Unemployment Rates to Manage Inventory

• Subjects: Business Management
• Words: 2141

Fuel Consumption for Cars Made in the US and Japan

• Subjects: Business Industry

Theoretical Stock Prices

• Subjects: Economics Investment

Supply Chain Design: Honda Gulf

• Words: 2999

Using Smartphones in Learning

• Subjects: Tech & Engineering Technology in Education
• Words: 6084

Action Research in Science Education

• Subjects: Education Writing & Assignments
• Words: 1199

Introduction to Nursing Research

• Subjects: Health & Medicine Healthcare Research

Students’ Perception of a Mobile Application for College Course

• Words: 1500

Carbon Fiber Reinforced Polymer Application

• Subjects: Construction Design
• Words: 1440

An Evaluation of the Suitability of ‘New Headway- Intermediate’ by Liz & John Soars

• Subjects: Education Pedagogical Approaches
• Words: 3456

Parenting Variables in Antenatal Education

• Subjects: Family Planning Health & Medicine
• Words: 1211

Sustained Organisational Learning Methods

• Words: 1416

The Achievement of Millennium Development Goals in India

• Subjects: International Relations Politics & Government

The EV Products in China

• Words: 1146

Green Energy Brand Strategy: Chinese E-Car Consumer Behaviour

• Subjects: Business Strategy
• Words: 3378

Binomial Logistic Regression

• Subjects: Math Sciences

Odds Ratio in Logistic Regression

Efficacy of antibiotic therapy and appendectomy, local food production in malaysia.

• Words: 1625

The Indian Agriculture Sector

• Subjects: Agriculture Sciences
• Words: 1662

Beer Market Trends in the UK

• Subjects: Business Marketing
• Words: 1374

Waste Management in Australia

• Subjects: Environment Recycling
• Words: 1851

Health and Environment in Abu Dhabi

• Subjects: Air Pollution Environment
• Words: 3126

The Relations Between Media and School Violence

• Subjects: Sociology Violence
• Words: 2832

BlackBerry Management Perspectives

• Words: 2831

Apple Inc. Equity Valuation

• Words: 3729

Zara Fashions’ Supply Chain

• Words: 6066

The Extent to Which FDI Inflows have Influenced GDPGrowth in India

• Subjects: Economic Trends Economics
• Words: 1780

Addicted 2 Football Business Plan

• Subjects: Business Company Analysis
• Words: 2514

Ashtead Group Plc Financial Accounting

• Words: 5733

Reaching the Critical Mass in eMarketplaces

• Subjects: Business E-Commerce
• Words: 2204

Independent Samples t-test with SPSS

Economics concepts: alfred marshall.

• Subjects: Economic Concepts Economics

Exploring Reliability and Validity

• Subjects: Psychological Issues Psychology

Sustaining Australia’s Rate of Economic Growth

• Subjects: Economic Systems & Principles Economics
• Words: 1356

E-Cig Project and Price Customization

• Subjects: Business Marketing Project

Public Relations and Customer Loyalty

• Subjects: Branding Business
• Words: 2118

Game-based Learning and Simulation in a K-12 School in the United Arab Emirates

• Subjects: Education Pedagogy
• Words: 3683

The Issue of Muslims’ Immigration to Australia

• Subjects: Immigration Sociology
• Words: 3492

China’s Energy and Environmental Implications

• Subjects: Ecology Environment
• Words: 3709

The Target Company

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The Effect of Social Media on Today’s Youth

• Subjects: Entertainment & Media Social Media Issues
• Words: 2165

Heineken Company in the US market

• Words: 1275

International Communication in Saudi Arabia

• Subjects: Communications Sociology
• Words: 1390

The Algerian Wool Company

• Words: 2570

Jewish Life in North America

• Subjects: Sociological Issues Sociology
• Words: 1788

Impact of Gambling on the Bahamian Economy

• Subjects: Economics Influences on Political Economy
• Words: 3871

International Marketing Plan for Tata Nano

• Subjects: Business Financial Marketing
• Words: 5299

Home Based and Community Based Services (HCBS)

• Subjects: Health & Medicine Healthcare Institution

Case of Ski Pro Corporation

• Subjects: Business Company Missions

Writing Quantitative Research Studies

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• Adyya Gupta 3 &
• Karen G. Peres 4  

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Summarizing quantitative data and its effective presentation and discussion can be challenging for students and researchers. This chapter provides a framework for adequately reporting findings from quantitative analysis in a research study for those contemplating to write a research paper. The rationale underpinning the reporting methods to maintain the credibility and integrity of quantitative studies is outlined. Commonly used terminologies in empirical studies are defined and discussed with suitable examples. Key elements that build consistency between different sections (background, methods, results, and the discussion) of a research study using quantitative methods in a journal article are explicated. Specifically, recommended standard guidelines for randomized controlled trials and observational studies for reporting and discussion of findings from quantitative studies are elaborated. Key aspects of methodology that include describing the study population, sampling strategy, data collection methods, measurements/variables, and statistical analysis which informs the quality of a study from the reviewer’s perspective are described. Effective use of references in the methods section to strengthen the rationale behind specific statistical techniques and choice of measures has been highlighted with examples. Identifying ways in which data can be most succinctly and effectively summarized in tables and graphs according to their suitability and purpose of information is also detailed in this chapter. Strategies to present and discuss the quantitative findings in a structured discussion section are also provided. Overall, the chapter provides the readers with a comprehensive set of tools to identify key strategies to be considered when reporting quantitative research.

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Ankur Singh

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Singh, A., Gupta, A., Peres, K.G. (2019). Writing Quantitative Research Studies. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_117

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Home » Quantitative Research – Methods, Types and Analysis

Quantitative Research – Methods, Types and Analysis

Table of Contents

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

• Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
• Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
• Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
• Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
• Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

• Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
• Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
• Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
• Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
• Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
• Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
• Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

• Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
• Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
• Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
• Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
• Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
• Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
• Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

• Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
• Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
• Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
• Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
• Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
• Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

• To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
• To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
• To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
• To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
• To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

• Description : To provide a detailed and accurate description of a particular phenomenon or population.
• Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
• Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
• Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

• Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
• Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
• Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
• Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
• Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
• Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

• Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
• Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
• Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
• Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
• Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
• Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.

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This article has a correction. Please see:

• Correction: How to appraise quantitative research - April 01, 2019

• Xabi Cathala 1 ,
• Calvin Moorley 2
• 1 Institute of Vocational Learning , School of Health and Social Care, London South Bank University , London , UK
• 2 Nursing Research and Diversity in Care , School of Health and Social Care, London South Bank University , London , UK
• Correspondence to Mr Xabi Cathala, Institute of Vocational Learning, School of Health and Social Care, London South Bank University London UK ; cathalax{at}lsbu.ac.uk and Dr Calvin Moorley, Nursing Research and Diversity in Care, School of Health and Social Care, London South Bank University, London SE1 0AA, UK; Moorleyc{at}lsbu.ac.uk

https://doi.org/10.1136/eb-2018-102996

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Introduction

Some nurses feel that they lack the necessary skills to read a research paper and to then decide if they should implement the findings into their practice. This is particularly the case when considering the results of quantitative research, which often contains the results of statistical testing. However, nurses have a professional responsibility to critique research to improve their practice, care and patient safety. 1  This article provides a step by step guide on how to critically appraise a quantitative paper.

Title, keywords and the authors

The authors’ names may not mean much, but knowing the following will be helpful:

Their position, for example, academic, researcher or healthcare practitioner.

Their qualification, both professional, for example, a nurse or physiotherapist and academic (eg, degree, masters, doctorate).

This can indicate how the research has been conducted and the authors’ competence on the subject. Basically, do you want to read a paper on quantum physics written by a plumber?

The abstract is a resume of the article and should contain:

Introduction.

Research question/hypothesis.

Methods including sample design, tests used and the statistical analysis (of course! Remember we love numbers).

Main findings.

Conclusion.

The subheadings in the abstract will vary depending on the journal. An abstract should not usually be more than 300 words but this varies depending on specific journal requirements. If the above information is contained in the abstract, it can give you an idea about whether the study is relevant to your area of practice. However, before deciding if the results of a research paper are relevant to your practice, it is important to review the overall quality of the article. This can only be done by reading and critically appraising the entire article.

The introduction

Example: the effect of paracetamol on levels of pain.

My hypothesis is that A has an effect on B, for example, paracetamol has an effect on levels of pain.

My null hypothesis is that A has no effect on B, for example, paracetamol has no effect on pain.

My study will test the null hypothesis and if the null hypothesis is validated then the hypothesis is false (A has no effect on B). This means paracetamol has no effect on the level of pain. If the null hypothesis is rejected then the hypothesis is true (A has an effect on B). This means that paracetamol has an effect on the level of pain.

Background/literature review

The literature review should include reference to recent and relevant research in the area. It should summarise what is already known about the topic and why the research study is needed and state what the study will contribute to new knowledge. 5 The literature review should be up to date, usually 5–8 years, but it will depend on the topic and sometimes it is acceptable to include older (seminal) studies.

Methodology

In quantitative studies, the data analysis varies between studies depending on the type of design used. For example, descriptive, correlative or experimental studies all vary. A descriptive study will describe the pattern of a topic related to one or more variable. 6 A correlational study examines the link (correlation) between two variables 7  and focuses on how a variable will react to a change of another variable. In experimental studies, the researchers manipulate variables looking at outcomes 8  and the sample is commonly assigned into different groups (known as randomisation) to determine the effect (causal) of a condition (independent variable) on a certain outcome. This is a common method used in clinical trials.

There should be sufficient detail provided in the methods section for you to replicate the study (should you want to). To enable you to do this, the following sections are normally included:

Overview and rationale for the methodology.

Participants or sample.

Data collection tools.

Methods of data analysis.

Ethical issues.

Data collection should be clearly explained and the article should discuss how this process was undertaken. Data collection should be systematic, objective, precise, repeatable, valid and reliable. Any tool (eg, a questionnaire) used for data collection should have been piloted (or pretested and/or adjusted) to ensure the quality, validity and reliability of the tool. 9 The participants (the sample) and any randomisation technique used should be identified. The sample size is central in quantitative research, as the findings should be able to be generalised for the wider population. 10 The data analysis can be done manually or more complex analyses performed using computer software sometimes with advice of a statistician. From this analysis, results like mode, mean, median, p value, CI and so on are always presented in a numerical format.

The author(s) should present the results clearly. These may be presented in graphs, charts or tables alongside some text. You should perform your own critique of the data analysis process; just because a paper has been published, it does not mean it is perfect. Your findings may be different from the author’s. Through critical analysis the reader may find an error in the study process that authors have not seen or highlighted. These errors can change the study result or change a study you thought was strong to weak. To help you critique a quantitative research paper, some guidance on understanding statistical terminology is provided in  table 1 .

• View inline

Some basic guidance for understanding statistics

Quantitative studies examine the relationship between variables, and the p value illustrates this objectively.  11  If the p value is less than 0.05, the null hypothesis is rejected and the hypothesis is accepted and the study will say there is a significant difference. If the p value is more than 0.05, the null hypothesis is accepted then the hypothesis is rejected. The study will say there is no significant difference. As a general rule, a p value of less than 0.05 means, the hypothesis is accepted and if it is more than 0.05 the hypothesis is rejected.

The CI is a number between 0 and 1 or is written as a per cent, demonstrating the level of confidence the reader can have in the result. 12  The CI is calculated by subtracting the p value to 1 (1–p). If there is a p value of 0.05, the CI will be 1–0.05=0.95=95%. A CI over 95% means, we can be confident the result is statistically significant. A CI below 95% means, the result is not statistically significant. The p values and CI highlight the confidence and robustness of a result.

Discussion, recommendations and conclusion

The final section of the paper is where the authors discuss their results and link them to other literature in the area (some of which may have been included in the literature review at the start of the paper). This reminds the reader of what is already known, what the study has found and what new information it adds. The discussion should demonstrate how the authors interpreted their results and how they contribute to new knowledge in the area. Implications for practice and future research should also be highlighted in this section of the paper.

A few other areas you may find helpful are:

Limitations of the study.

Conflicts of interest.

Table 2 provides a useful tool to help you apply the learning in this paper to the critiquing of quantitative research papers.

Quantitative paper appraisal checklist

• 1. ↵ Nursing and Midwifery Council , 2015 . The code: standard of conduct, performance and ethics for nurses and midwives https://www.nmc.org.uk/globalassets/sitedocuments/nmc-publications/nmc-code.pdf ( accessed 21.8.18 ).
• Gerrish K ,
• Moorley C ,
• Tunariu A , et al
• Shorten A ,

Competing interests None declared.

Patient consent Not required.

Provenance and peer review Commissioned; internally peer reviewed.

Correction notice This article has been updated since its original publication to update p values from 0.5 to 0.05 throughout.

Linked Articles

• Miscellaneous Correction: How to appraise quantitative research BMJ Publishing Group Ltd and RCN Publishing Company Ltd Evidence-Based Nursing 2019; 22 62-62 Published Online First: 31 Jan 2019. doi: 10.1136/eb-2018-102996corr1

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Strengths and Weaknesses of Quantitative and Qualitative Research

There are many types of research taking place, which results in the evolution of something new and unique. Traditional Marketing Research has two options to conduct its research: Quantitative and Qualitative methods .  

What is Quantitative Research

Quantitative research is defined as an organized analysis of occurrences by collecting measurable data and applying statistical, mathematical, and computational methodologies. It is the process of gathering information from existing and potential customers by sampling methods and the distribution of online surveys, questionnaires, online polls, and so on. The results of these polls or surveys are represented numerically. 

Quantitative research is dependent on the creation of a Hypothesis followed by an accurate analysis of the statistics in order to understand and explain the research findings. It focuses more on the quantity of things and their statistical patterns. Using the number comes to analysis so as to come to a conclusion.

After gaining a thorough understanding of these figures, it is possible to forecast the future of a product or service and make modifications as needed.

Strengths of Quantitative Research

The quantitative research method has proven to be beneficial in the following ways

• It provides an allowance for the formulation of statistically sound
• Quantitative data provides a macro view with all the required details and comparatively larger samples.
• Larger sample sizes enable the conclusion to be generalized.
• Evaluation of the multiple data sets can be done at once and that too at a faster pace and accurately.
• This method is called to be appropriate when there is a need for systematic and standardized comparisons.
• The manual implementations of ideas can be automated completely which can save time.

Weaknesses of Quantitative Data

Here are some of the weaknesses of quantitative research:

• The quantitative method reveals what and to what extent but often fails to answer more on why and how.
• This type of research requires the model performance to be monitored on a constant basis in order to ensure its compliance with the original hypotheses.
• The impression of homogeneity in a sample may turn out to be fake in this method.
• This method involves a limited number of Quants supply and also involves complex disciplines which are hard to master.

Types of Quantitative Research Methods

When it comes to gathering information, quantitative research comes in handy. It provides you with a wide range of options. Each has its own set of pros and cons. Hence, it is advised to use a combination of them to get the best outcomes. Here are the four commonly used quantitative research methods that you can consider employing:

Conducting surveys is one of the most common quantitative research methods that most marketers utilize. In this method, marketers distribute surveys to their target audience in order to gather information, followed by statistical analysis of the results in order to develop conclusions and insights. 

In addition to being a short turnaround method, it is an excellent approach to better understand your target customers or explore a new market. Here are the best ways to conduct surveys: 

• a. Survey via Email: The use of email to communicate with a large number of individuals is quick and can be more cost-effective than the other methods outlined in this section.
• b. Phone Campaign : Not everyone has access to the internet, so if you want to reach a specific audience that may find it difficult to interact in this manner (for example, older consumers), a telephone campaign may be a more effective strategy. However, phone campaigns can be expensive endeavours as you’ll have to employ teams for calling your consumers and taking their answers. Also, there will be increased telephone bills as well as a result.
• c. Postal Surveys : like the phone, it allows you to contact a large portion of the population, but it is expensive and takes a long time to complete the task. As businesses strive to discover and respond to changes in consumer behaviour as quickly as possible, postal surveys have grown increasingly out of date.
• d. Distribution through social media: Social media handles are another wonderful ways to conduct surveys. By distributing the survey through social media, you can collect a greater number of replies from those who are familiar with the brand.

Related: Quantitative And Qualitative Research Tools And Techniques

• e. QR codes: You can use QR codes by printing or publishing them in magazines, on signs, business cards, or on almost any other object or medium you like.
• f. SMS-based survey: SMS-based surveys can help you collect a large number of responses quickly and efficiently in a short amount of time.
• g. In-person quantitative research : doing quantitative research in person makes sense in particular situations. However, this is not the solution for all types of research. In-person quantitative research works well when you need to capture quantifiable data about a customer’s experience in the present, or intercepts, where you need customers to physically engage with a product in order to provide relevant feedback. However, know that these kinds of research are costly affairs, as well as time-consuming and challenging to organize and carry out logistically.

In this approach, you’ll be able to collect information that may be categorized and analyzed in a quantitative, numerical manner.

2. Correlation Research

Correlation research examines the effects of one entity on another and the changes that result. This quantitative research method requires a minimum of two different groups or entities to establish the relationship.

This quantitative research strategy uses mathematical analysis to correlate two or more variables. The original patterns, correlations, and trends between variables are finished. Impact of one variable on the other and how it affects the interaction between them are observed. To achieve desired findings, researchers often modify one of the variables.

It is best not to draw conclusions just from correlational data. Because two variables that are in sync are not necessarily connected.

3. Causal-Comparative Research

This strategy relies heavily on comparison. This quantitative research method is used to determine the cause-effect relationship between two or more variables, where one variable is dependent on the other. 

In this step, the independent variable is established but not changed. The variables or groupings must be formed as in nature. Because dependent and independent variables always exist in a group, it is prudent to draw conclusions carefully considering all elements.

Causal-comparative research examines how distinct variables or groups change as a result of the same changes. This study is undertaken regardless of the relationship between two or more variables. Statistical analysis is used to clearly present the results of quantitative research.

4. Experimental Research

True experimentation is based on a theory. Experimental research, as the name implies, tests one or more hypotheses. This theory is unproven and only a supposition. In experimental research, the statement is tested to see if it is true. Experiment research might have numerous theories. One can verify or deny a theory.

RESULT ANALYSIS

Once you’ve obtained your data, the next step is to categorize and evaluate the information. There are numerous approaches that can be used to do this. However, 

Cross-tabulation is a powerful technique that categorizes your results depending on demographic subgroups, which is very useful. 

For example, how many of the persons who answered ‘yes’ to a question were adults and how many were youngsters can be calculated.

Take the time to clean the data (for example, deleting respondents who rushed through the survey and repeatedly selected the same answer) to ensure that you can draw confident inferences from it. All of this can be handled by a competent group of professionals.

Pointers to Keep in Mind While Constructing Surveys

• Make it crystal clear what you want to accomplish with your survey. 
• This will assist you in determining your target audience and in developing relevant queries for them.
• Make use of easy and simple language that people from a variety of backgrounds may easily comprehend.
• Make sure your questions and answers are concise and easy to understand.
• Use acronyms only if you are confident that your audience will understand what you are trying to say.
• Make sure not to over-survey your participants. Instead, make an effort to obtain as much information as possible in the first instance—excessive surveying results in survey weariness, which results in a poor response rate.
• Make certain that all critical questions have been marked as obligatory.
• Avoid using double negatives in your questions. Participants may become confused if you utilize double negatives in your questions, and they may misinterpret your queries.
• Providing a ‘not applicable’ response option will assist you in collecting correct information.
• Instead of a four-point scale, a five-point scale should be used because the latter does not provide a neutral answer choice.
• Include closed-ended questions rather than open-ended questions. An ideal survey should primarily include closed-ended questions, with a few open-ended questions thrown in for good measure.
• Example: instead of asking, “Can you tell us about your experience with our food delivery services?” You should ask, “How happy are you with our food delivery services?” 
• Your options may include the following: “Very Happy / Satisfied / Don’t know / Dissatisfied / Very Dissatisfied” 

Why is quantitative research important to business?

Quantitative research is an extremely useful tool for anyone who wants to have a better understanding of their market and clients. The ability to acquire trustworthy, objective insights from data and clearly identify trends and patterns is enabled by this technology.

Quantitative research is a critical component of market research; it depends on hard facts and numerical data to create an objective picture of people’s ideas as possible to obtain an understanding of their preferences. There are numerous reasons why quantitative research is essential in any market research plan , including the following:

• It makes it possible to conduct research on a large scale.
• It assists organizations in determining the scale of a new opportunity.
• It allows marketers to quickly and simply compare distinct groups (e.g., by age, gender, or market) in order to discover the similarities and variations between them.
• It can be useful when trying to simplify a complicated problem or topic into a small number of variables.

Importance of quantitative research in marketing

The quantitative study is mainly concerned with numbers. It makes use of mathematical analysis and data to throw light on vital facts pertaining to your company and the market in general. This type of information, obtained using techniques such as multiple-choice questionnaires or surveys, can be used to generate buzz in your organization and its products and services.

Related: How to Use Customer Data Analytics for Higher ROI

What is Qualitative Research

The methodologies utilized in qualitative research may appear ineffectual to individuals who are more experienced with quantitative research approaches at first glance. 

It is more focused on exploring the issues, understanding the actual problem, and enabling oneself to answer all the questions. The qualitative Research Method is more dependent on deriving the value of variables in their natural setting. 

In a nutshell, qualitative research differs from quantitative research in that it emphasizes words rather than statistics and depth rather than breadth. 

Its approaches are exploratory in nature, intending to uncover the opinions, thoughts, and feelings of those who participate.  It is most frequently used to inform the development of new concepts, theories, and products. Qualitative research, which was originally designed for use in the social sciences, is now commonly utilized to inform market research by acquiring unique consumer insight from a large amount of available data.

Strengths of Qualitative Research

Qualitative research can be beneficial in the following ways

• All the problems and the topics covered in this research are in detail.
• This method majorly focuses on small groups which ultimately do not require more expenses when compared to quantitative research.
• With the emergence of new developed information and findings, the revision, direction and framework of the data can be done easily and quickly.
• The data is collected from a small group which bounds it to be universal for a large population.
• The data with this method is collected based on genuine efforts and gives a clear vision of what can be expected.

Weaknesses of Qualitative Research

• As the data is collected for a small group, which assumptions cannot be made beyond the small group of people.
• It becomes difficult to demonstrate, maintain and assess the rigidity of the data.
• The collection of statistical data is not easy and cannot be done solely by using this method.
• As the data is in big quantity, analysis and interpretation of the data take much time.
• The responses of the subjects might be affected as the researchers are bound to be present during the process of data gathering.

Types of Qualitative Research Method

There are 8 types of Qualitative Methods; take a look…

1. One-on-one Interview

In-depth interviews are a typical qualitative research method. It involves a one-on-one interview with one respondent. This is essentially a conversational strategy that allows for detailed responses.

This strategy allows for exact data collection regarding people’s beliefs and motivations. Asking the appropriate questions can help a researcher acquire valuable data. If the researchers require further information, they should ask follow-up questions.

One-on-one interviews can be conducted in person or over the phone and can last from 30 minutes to two hours. Face-to-face interviews allow for better reading of respondents’ body language and matching of responses.

2. Focus Groups

A focus group is yet another popular qualitative data collection strategy. It typically includes 6-10 people from your target market. The focus group’s major goal is to answer “why,” “what,” and “how.” 

Focus groups have the advantage of not requiring face-to-face interaction. Focus groups can now be issued online surveys on multiple devices, and responses can be collected instantly. 

However, know that this is one of the more costly online qualitative research approaches. They usually explain complex processes. This strategy is great for market research and concept testing.

3. Discussion Boards

Similar to focus groups, discussion boards effectively collect dynamic data over time. Like an online forum , the researcher can initiate a debate and invite participants to add and expand on one other’s ideas. Using prompts and probes, the researcher can have as much or as little input as needed. A forum can be active for days or weeks.

Marketers can use these approaches to get feedback on a new product. Also, these techniques can help marketers grasp different perspectives on the product and can get to know their customers.

4. Case-study

In recent years, the case study approach has evolved into a robust qualitative research method. This is considered one of the best methods to describe an organization or entity.

This research strategy is employed in fields like education and social sciences. This method may appear complex, but it is one of the simplest to use because it requires a complete understanding of data gathering methods and data inference.

5. Pictures and Videos 

Pictures and videos are also interactive qualitative approaches. This is, in fact, one of the most popular qualitative research strategies today. Respondents can contribute photographs or videos to illustrate their stories. Respondents could, for example, give video footage together with a written evaluation of a product.

6. Record-Keeping or Logging

This strategy uses existing reputable documents and information sources as data sources. One can look through books and other reference material to gather data for the research in this method.

7. Ethnographic study

It is the most in-depth approach to studying people in their natural habitat. An organization, a city, or a remote place could be the target audience for this strategy. 

Cultures, difficulties, motivations, and contexts are studied in this study. Geographical constraints can affect data collection. Instead of interviews and debates, you get to see the natural environment.

This type of research might range from a few days to a few years because it includes close observation and data collection. It is a time-consuming and challenging strategy that relies on the researcher’s ability to examine, observe, and deduce the data.

8. Observation Method

Lastly, in the list, we have the observation method. This is a method of collecting data using subjective methods. Researchers use subjective approaches to gather qualitative data to obtain information or data. Qualitative observation is used to compare quality.

It involves characteristics, not measures. Sight, smell, touch, taste, and hearing are all examples of qualitative observation.

It is necessary to do an in-depth analysis of your qualitative data after it has been collected in order to identify the essential themes and insights from your research.

Once the qualitative research is completed and the essential insights have been identified, the next step is to utilize the same insights in the subsequent stages of developing a product or marketing strategy. Moreover, you can use these insights to narrow down your target audience.

Aside from that, your research may have elicited some new ideas and notions that you would like to investigate further, forming the basis for quantitative analysis to determine whether these viewpoints represent the general public.

Related Post: Key Difference Between Database and Data Warehouse

Why Do You Need Qualitative Research?

In contrast to a closed question survey, qualitative procedures provide a unique level of information that is impossible to obtain via a quantitative survey. Respondents are free to share their own experiences, opinions, and feelings without feeling compelled to do so

Qualitative methods provide a more dynamic approach to research because they allow the researcher to follow up on responses given by respondents in real-time, resulting in valuable conversation around a topic that would not otherwise be possible with a structured survey. 

When it comes to capturing accurate and in-depth insights, qualitative research methodologies are the go-to method for researchers. 

It is extremely beneficial to record “factual facts.” Here are some examples of when qualitative research should be conducted.

• When developing a new product or producing a new concept
• Evaluating your product, brand, or service in order to improve your marketing approach
• To better understand how your target audience reacts to marketing campaigns and other communications.
• To recognize your own personal strengths and flaws
• Understanding customers’ purchase behavior  
• To explore market demographics, segments, and customer groups. 
• To obtain information on the public’s perception of a brand, company, or product.

The Bottom Line

So, this is all about qualitative research and quantitative research. Based on the above discussion, it is safe to say that Qualitative research makes up for what quantitative research lacks in terms of meaning depth. Having access to both types of research methods allows for the fulfilment of all research needs. 

In a nutshell, qualitative methods complement quantitative research approaches perfectly. Together, they present a once-in-a-lifetime chance for businesses to gather detailed information on their customers, which they can use to better their marketing efforts and increase their bottom line.

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