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Hypothesis Testing

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• 1. Multiple Choice Edit 30 seconds 1 pt The following are methods used to test hypotheses except: traditional (computed value) method p-value method confidence interval method survey method
• 2. Multiple Choice Edit 45 seconds 1 pt What hypothesis states equality or no difference, or no relationship/effect? statistical hypothesis null hypothesis alternative hypothesis
• 3. Multiple Choice Edit 45 seconds 1 pt What hypothesis states no equality or existence of differences, relationship, or effect? statistical hypothesis null hypothesis alternative hypothesis
• 4. Multiple Choice Edit 30 seconds 1 pt Which hypothesis is generally formulated to look for evidence to support a claim called a research hypothesis? statistical hypothesis null hypothesis alternative hypothesis
• 5. Multiple Choice Edit 45 seconds 1 pt In reality, the null hypothesis may or may not be true, and a decision is made to reject or not to reject it on the basis of the data obtained from a sample. True False
• 6. Multiple Choice Edit 30 seconds 1 pt The level of significance is the maximum probability of committing a type II error. True False
• 7. Multiple Choice Edit 45 seconds 1 pt A level of significance of 5% means: There's a 5% chance we're wrong There's a 5% chance we'll be wrong if we fail to reject the null hypothesis There's a 5% chance we'll be wrong if we reject the null hypothesis. There's a 5% chance you'll get an A on the test.
• 8. Multiple Choice Edit 45 seconds 1 pt Which value separates the critical region from the noncritical region in a normal curve when testing the hypothesis? computed value t-value z-value critical value
• 9. Multiple Choice Edit 3 minutes 1 pt Which of the following shows a right-tailed test? H 1 : µ < 15 H 0 : µ < 15 H 1 : µ > 15 H 0 : µ > 15
• 10. Multiple Choice Edit 3 minutes 1 pt Which of the following shows a left-tailed test? H 1 : µ < 15 H 0 : µ >15 H 1 : µ > 15 H 0 : µ > 15
• 11. Multiple Choice Edit 45 seconds 1 pt A Type I error is when:  We obtain the wrong test statistic We reject the null hypothesis when it is actually true We fail to reject the null hypothesis when it's actually false We reject the alternate hypothesis when it's actually true
• 14. Multiple Choice Edit 45 seconds 1 pt A level of significance of 5% means: There's a 5% chance we're wrong There's a 5% chance we'll be wrong if we fail to reject the null hypothesis There's a 5% chance we'll be wrong if we reject the null hypothesis. There's a 5% chance you'll get an A on the test.
• 15. Multiple Choice Edit 45 seconds 1 pt Which of the following is not an option for an  alternative  hypothesis?  Ha = k Ha > k Ha < k Ha ≠ k
• 16. Multiple Choice Edit 45 seconds 1 pt A car manufacturer advertises that its new subcompact models get 47 mpg. If μ is the mileage of these cars, what could be the null and alternate hypothesis if we wanted to check if the car's mpg is overrated?  H0  = 47 Ha  = 47 H0  = 47 Ha  > 47 H0  = 47 Ha  < 47 H0  = 47 Ha  ≠ 47
• 17. Multiple Choice Edit 30 seconds 1 pt  A result was said to be significant at the 5% level. This means: the null hypothesis is probably wrong the result would be unexpected if the null hypothesis were true the null hypothesis is probably true none of the above
• 18. Multiple Choice Edit 45 seconds 1 pt What does it mean to say a test is two-tailed? There is no predicted direction for the alternative hypothesis There are two alternative hypotheses There are two types of error
• 19. Multiple Choice Edit 30 seconds 1 pt  Failing to reject a null hypothesis that is false can be characterized as a Type I error a Type II error both a Type I and Type II error no error
• 20. Multiple Choice Edit 45 seconds 1 pt A Type I error is when:  We reject the null hypothesis when it is actually true We obtain the wrong test statistic We fail to reject the null hypothesis when it's actually false We reject the alternate hypothesis when it's actually true
• 21. Multiple Choice Edit 45 seconds 1 pt A P-value indicates: the probability that the null hypothesis is true the probability of obtaining the results (or one more extreme) if the null hypothesis is true the probability that the alternative hypothesis is true probability of a Type I error
• 22. Multiple Choice Edit 45 seconds 1 pt What separates the critical region from the noncritical region? critical value computed value z-score
• 23. Multiple Choice Edit 30 seconds 1 pt Type I error is also called beta error alpha error critical value error
• 24. Multiple Choice Edit 45 seconds 1 pt Which of the following yields correct decision? Accept a false null hypothesis Reject a true null hypothesis Accept a true null hypothesis
• 25. Multiple Choice Edit 30 seconds 1 pt If the test is two-tailed, the critical region, with an area  equal to α, will be on the left side of the mean .  True False

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Marketing Research: Planning, Process, Practice

Student resources, multiple choice quizzes.

Try these quizzes to test your understanding.

1. Research analysis is the last critical step in the research process.

2. The final research report where a discussion of findings and limitations is presented is the easiest part for a researcher.

3. Two different researchers may be presented with the same data analysis results and discuss them differently, uncovering alternative insights linked to the research question, each using a different lens.

4. A reliable research is essentially valid, but a valid research is not necessarily reliable.

5. A valid research refers to the degree to which it accurately measures what it intends to measure.

6. Keeping an envisioned original contribution to knowledge in mind, the research report in appearance and content should highlights the outcomes and link back to objectives.

7. A good conclusion chapter should (please select ALL answers that apply) ______.

• have a structure that brings back what the research set out to do
• discuss the researcher’s own assumptions and ideas about the topic under study
• makes logical links between the various parts of the arguments starting from the hypotheses

Answer: A & C 

8. Research implications presented in a study must be either theoretical only or practical only.

9. Good researchers should aim for a perfect research, with no limitations or restrictions.

10. Examples of research limitations include (please select the answer that DOESN’T apply) ______.

• access to the population of interest
• the study’s coverage of possible contributory factors
• the researcher’s poor analysis skills
• the sampling technique used

11. A good structure outlining an effective research report starts with the ‘Analysis and Results’ section.

12. A good research study can just focus on its key outcomes without highlighting areas for future research.

13. If some of the research questions were not answered or some research objectives could not be achieved, then the final report must explain and reflect on the reasons why this is the case.

14. The importance of being critically reflective in presenting the future research section is that it allows for the advent of new arenas of thought that you or other researchers can develop on.

15. A weak future research section and weak discussion of the research limitations does not make the study fragile/lacking rigour and depth.

16. Once a research specifies a study’s limitations, this discredits all research efforts exerted in it.

17. Reporting research is about presenting the research journey through clear and evidence-based arguments of design, process and outcomes, not just describing it.

18. It is not important to present in every research report the ethical considerations that were anticipated or have ascended in the study.

19. Verbal and visual presentations of research aid in the dissemination of its outcomes and value, and allow for its strengths to be revealed.

20. In oral presentations, the audience expects you as a researcher to present your work in full detail even if they will ask further questions in the follow-up discussion.

What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples

By:  Derek Jansen (MBA)  | Reviewed By: Dr Eunice Rautenbach | June 2020

If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .

“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing. 

Research Hypothesis 101

• What is a hypothesis ?
• What is a research hypothesis (scientific hypothesis)?
• Requirements for a research hypothesis
• Definition of a research hypothesis
• The null hypothesis

What is a hypothesis?

Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:

Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.

In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:

Hypothesis: sleep impacts academic performance.

This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.

But that’s not good enough…

Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .

What is a research hypothesis?

A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .

Let’s take a look at these more closely.

Need a helping hand?

Hypothesis Essential #1: Specificity & Clarity

A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).

Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.

Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.

Hypothesis Essential #2: Testability (Provability)

A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.

For example, consider the hypothesis we mentioned earlier:

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.  

We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference. 

Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?

So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂

Defining A Research Hypothesis

You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.

A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.

So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.

What about the null hypothesis?

You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.

For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.

At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.

And there you have it – hypotheses in a nutshell. 

If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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16 Comments

Very useful information. I benefit more from getting more information in this regard.

Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc

In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin

This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.

Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?

It’s a counter-proposal to be proven as a rejection

Please what is the difference between alternate hypothesis and research hypothesis?

It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?

In qualitative research, one typically uses propositions, not hypotheses.

could you please elaborate it more

I’ve benefited greatly from these notes, thank you.

This is very helpful

well articulated ideas are presented here, thank you for being reliable sources of information

Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)

I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?

this is very important note help me much more

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The effectiveness of Quizizz learning media in strengthening numeric ability children

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Wiwik Hatoliya Syariatul Hidayah , Sri Slamet; The effectiveness of Quizizz learning media in strengthening numeric ability children. AIP Conf. Proc. 17 January 2024; 2926 (1): 020077. https://doi.org/10.1063/5.0185085

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This research is motivated by the use of learning media which is one of the facilities and infrastructure to support school activities. With the use of appropriate learning media will be able to have an impact on children's learning outcomes. This research aims to determine the effectiveness of using Quizizz learning media in strengthening the numerical abilities of children aged 4-5 years. This type of research is quantitative research with the True Experimental method by conducting pre-test and post-test to measure the acquisition of the treatment (treatment) on the object of research. The samples taken in this study were children aged 4-5 years in TK A2 class in TK IA as many as 18 children. Retrieval of research data using validity tests and online questions. The data analysis technique used is the validity test for media and Quizizz materials and comparative statistics for online questions. The results of the validity test for media and materials in Quizizz show that Quizizz is valid and can be used as a learning medium in kindergarten. The result of comparative statistics is to test the hypothesis that there is a difference between two (or more) variables being studied in the implementation of online questions during the pre-test and post-test. The hypothesis states that there is a strengthening of the numerical ability of the research object after the use of Quizizz learning media. This can be seen from the results of the t test where t count > t table at a significant level of 5% (of 15.52).

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The Effect of Cognitive Assessment using the Quizizz Application on the Motivation and Minimum Competence of Elementary School Students

2023, https://www.ijrrjournal.com/IJRR_Vol.10_Issue.3_March2023/IJRR-Abstract58.html

This research was conducted by looking at the results of the assessment of low motivation, which impacts the low competence of the minimum achievement of students. Aims to analyze the effect of cognitive evaluations using the quizizz Application on elementary school students' motivation and minimum achievement. This research method uses quasi-experimental quantitative, with a quasi-experimental control group design. Data analysis techniques using normality tests, homogeneity, instrument validation, analysis of test results, and hypothesis testing. The study results concluded that the normality test for the experimental class was 0.000 and the control class was 0.000, so the experimental and control class data were normally distributed. 80.30 to 84.90 and the initial experimental class by 62.52 to 72.00, it can be concluded that the experimental class increased by 4.60 and the control class by 9.48, test the hypothesis using t-test db = N-2 = 50-2 = 48 at 5% confidence level obtained t table = 1.671. The result of the t count is more significant than the t table (7,975 > 1,671). With db = N-2 = 50-2 = 48 at the 5% confidence level, t table = 1,671 is obtained. The result of the t count is more significant than the t table (6.080 > 1.671), thus stating a correlation between assessment using the quizizz Application on students' motivation and achievement of minimum competencies.

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A test of the trait-consistent, affect regulation hypothesis with respect to agreeableness

• Published: 03 June 2024

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• Eugene W. Mathes   ORCID: orcid.org/0000-0003-2556-9327 1  

The trait-consistent, affect regulation hypothesis states that people seek to maintain affective states that are consistent with their traits. To date, most of the research has focused on neuroticism, extroversion, and related traits, like depression and low self-esteem, and has found that neurotics seek experiences that produce negative affect and extroverts seek experiences that produce positive affect. The purpose of this research was to apply this hypothesis to another one of the Big Five traits, agreeableness. It was hypothesized that agreeable people would seek experiences that made them feel agreeable and that disagreeable people would seek experiences that would make them feel disagreeable. Two studies were carried out in which participants completed trait measures of agreeableness. They then listed their favorite entertainments and rated the extent to which the entertainments made them feel agreeable. Support was found for the hypothesis that trait agreeable people choose entertainments than made them feel agreeable while trait disagreeable people choose entertainments that made them feel disagreeable. Thus, the trait-consistent, affect regulation hypothesis was found to also apply to agreeableness.

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The manuscript contains no individual person’s data in any form (including any individual details, images or videos). The data and other relevant materials are available on Open Science Framework.

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A self-reinforcing cycle hypothesis in heart failure pathogenesis

• Carlos Fernandez-Patron   ORCID: orcid.org/0000-0002-8033-0645 1 ,
• Gary D. Lopaschuk   ORCID: orcid.org/0000-0003-1010-0454 2 &
• Eugenio Hardy   ORCID: orcid.org/0000-0002-8351-4255 3  

Nature Cardiovascular Research ( 2024 ) Cite this article

Metrics details

• Energy metabolism
• Heart failure
• Metabolic diseases
• Multienzyme complexes

Heart failure is a progressive syndrome with high morbidity and mortality rates. Here, we suggest that chronic exposure of the heart to risk factors for heart failure damages heart mitochondria, thereby impairing energy production to levels that can suppress the heart’s ability to pump blood and repair mitochondria (both energy-consuming processes). As damaged mitochondria accumulate, the heart becomes deprived of energy in a ‘self-reinforcing cycle’, which can persist after the heart is no longer chronically exposed to (or after antagonism of) the risk factors that initiated the cycle. Together with other previously described pathological mechanisms, this proposed cycle can help explain (1) why heart failure progresses, (2) why it can recur after cessation of treatment, and (3) why heart failure is often accompanied by dysfunction of multiple organs. Ideally, therapy of heart failure syndrome would be best attempted before the self-reinforcing cycle is triggered or designed to break the self-reinforcing cycle.

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Cardiovascular Research Centre, Department of Biochemistry, Faculty of Medicine and Dentistry, College of Health Sciences, University of Alberta, Edmonton, Alberta, Canada

Carlos Fernandez-Patron

Cardiovascular Research Centre, Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada

Gary D. Lopaschuk

Center of Molecular Immunology, Havana, Cuba

Eugenio Hardy

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C.F.-P. conceived the hypothesis. C.F.-P. and E.H. conceived, wrote and edited the manuscript and drafted the figures. G.D.L. made key edits and additions to the intellectual content and figures. All authors contributed to the critical analysis of the literature.

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Fernandez-Patron, C., Lopaschuk, G.D. & Hardy, E. A self-reinforcing cycle hypothesis in heart failure pathogenesis. Nat Cardiovasc Res (2024). https://doi.org/10.1038/s44161-024-00480-6

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Received : 04 January 2024

Accepted : 25 April 2024

Published : 03 June 2024

DOI : https://doi.org/10.1038/s44161-024-00480-6

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Rethinking the sun's cycles: New physical model reinforces planetary hypothesis

by Simon Schmitt, Helmholtz Association of German Research Centres

Researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and the University of Latvia have posited the first comprehensive physical explanation for the sun's various activity cycles. It identifies vortex-shaped currents on the sun, known as Rossby waves, as mediators between the tidal influences of Venus, Earth as well as Jupiter and the sun's magnetic activity.

The researchers therefore present a consistent model for solar cycles of different lengths—and another strong argument to support the previously controversial planetary hypothesis. The results have now been published in the journal Solar Physics .

Although the sun, being near to us, is the best researched star, many questions about its physics have not yet been completely answered. These include the rhythmic fluctuations in solar activity . The most famous of these is that, on average, the sun reaches a radiation maximum every eleven years—which experts refer to as the Schwabe cycle.

This cycle of activity occurs because the sun's magnetic field changes during this period and eventually reverses polarity. This, in itself, is not unusual for a star—if it weren't for the fact that the Schwabe cycle is remarkably stable.

The Schwabe cycle is overlaid by other, less obvious fluctuations in activity ranging from a few hundred days to several hundred years, each named after their discoverers. Although there have already been various attempts to explain these cycles and mathematical calculations, there is still no comprehensive physical model.

Planets set the beat

For some years, Dr. Frank Stefani of HZDR's Institute of Fluid Dynamics has been an advocate of the "planetary hypothesis" because it is clear that the planets' gravity exerts a tidal effect on the sun, similar to that of the moon on the Earth. This effect is strongest every 11.07 years: whenever the three planets Venus, Earth and Jupiter are aligned with the sun in a particularly striking line, comparable to a spring tide on Earth when there is a new or full moon. This coincides conspicuously with the Schwabe cycle.

The sun's magnetic field is formed by complex movements of the electrically conducting plasma inside the sun. "You can think of it like a gigantic dynamo. While this solar dynamo generates an approximately 11-year activity cycle in its own right, we think the planets' influence then intervenes in the workings of this dynamo, repeatedly giving it a little push and thus forcing the unusually stable 11.07-year rhythm on the sun," Stefani explains.

Several years ago, he and his colleagues discovered strong evidence of a clocked process of this kind in the available observation data. They were also able to correlate various solar cycles with the movement of the planets just using mathematical methods. At first, however, the correlation could not be sufficiently explained physically.

Rossby waves on the sun act as intermediaries

"We have now found the underlying physical mechanism. We know how much energy is required to synchronize the dynamo, and we know that this energy can be transferred to the sun by so-called Rossby waves. The great thing is that we can now not only explain the Schwabe cycle and longer solar cycles but also the shorter Rieger cycles that we hadn't even considered previously," says Stefani.

Rossby waves are vortex-shaped currents on the sun similar to the large-scale wave movements in the Earth's atmosphere that control high- and low-pressure systems.

The researchers calculated that the tidal forces during the spring tides of two of each of the three planets Venus, Earth and Jupiter had exactly the right properties to activate Rossby waves—an insight with many consequences.

First of all, these Rossby waves then achieve sufficiently high speeds to give the solar dynamo the necessary impetus. Second, this occurs every 118, 193 and 299 days in accordance with the Rieger cycles that have been observed on the sun. And thirdly, all additional solar cycles can be calculated on this basis.

All cycles explained by a single model

This is where mathematics comes in: The superimposition of the three short Rieger cycles automatically produces the prominent 11.07-year Schwabe cycle. And the model even predicts long-term fluctuations of the sun because the movement of the sun around the solar system's center of gravity causes a so-called beat period of 193 years on the basis of the Schwabe cycle.

This corresponds to the order of magnitude of another cycle that has been observed, the Suess-de Vries cycle.

In this context, the researchers discovered an impressive correlation between the 193-year period that had been calculated and periodic fluctuations in climate data. This is another robust argument for the planetary hypothesis because "the sharp Suess-de Vries peak at 193 years can hardly be explained without phase stability in the Schwabe cycle, which is only present in a clocked process," Stefani estimates.

Does this mean the question as to whether the sun follows the planets' beat has finally been answered? Stefani says, "We'll probably only be 100% certain when we have more data. But the arguments in favor of a process clocked by the planets are now very strong."

Journal information: Solar Physics

Provided by Helmholtz Association of German Research Centres

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