Related Experiment Video
Updated: Feb 24, 2026
09:13
Hypoxia Alters miRNAs Levels Involved in Non-Mendelian Inheritance of Autism Spectrum Disorder in Mice
Published on: July 11, 2025
31.1K
When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment
Denes Szucs1, John P A Ioannidis2
1Department of Psychology, University of CambridgeCambridge, United Kingdom.
Frontiers in Human Neuroscience
|August 22, 2017
Summary
Null hypothesis significance testing (NHST) has shortcomings contributing to the replication crisis. Researchers should move beyond NHST as the default statistical method in biomedical and psychological sciences.
Area of Science:
- Statistics in biomedical and psychological research.
Background:
- Null hypothesis significance testing (NHST) is widely used but faces criticism.
- NHST shortcomings are implicated in the replication crisis across scientific disciplines.
Purpose of the Study:
- To review the limitations of NHST.
- To advocate for a shift away from NHST as the default statistical approach.
- To propose alternative statistical practices and research standards.
Main Methods:
- Review of existing literature on NHST limitations.
- Analysis of the impact of NHST on scientific reproducibility.
- Formulation of recommendations for statistical practices.
Main Results:
- NHST has inherent limitations that can hinder robust scientific inquiry.
- The default use of NHST contributes to the replication crisis.
- Alternative inferential methods are better suited for various research questions.
Conclusions:
- NHST should not remain the dominant statistical practice in biomedical and psychological research.
- Researchers should justify NHST use, publish power calculations, effect sizes, and negative findings.
- Pre-registration of studies and data sharing are crucial for reproducibility.
- Statistics education needs reform to phase out the "statistics lite" approach and promote better inferential methods.
Related Concept Videos
01:04Significance Testing: Overview
12.8K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
12.8K
01:14Decision Making: Traditional Method
5.6K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.6K
01:16Statistical Hypothesis Testing
7.0K
Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
7.0K
01:17Hypothesis: Accept or Fail to Reject?
29.7K
The outcome of any hypothesis testing leads to rejecting or not rejecting the null hypothesis. This decision is taken based on the analysis of the data, an appropriate test statistic, an appropriate confidence level, the critical values, and P-values. However, when the evidence suggests that the null hypothesis cannot be rejected, is it right to say, 'Accept' the null hypothesis?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
29.7K
01:14Errors In Hypothesis Tests
6.1K
When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
6.1K
01:16Null and Alternative Hypotheses
12.9K
The actual hypothesis testing begins by considering two hypotheses. They are termed the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
12.9K