Related Experiment Video
Updated: Jun 6, 2026

A Standardized Protocol for Preference Testing to Assess Fish Welfare
Published on: February 22, 2020
The use of one- versus two-tailed tests to evaluate prevention programs
Chris Ringwalt1, M J Paschall, Dennis Gorman
1Pacific Institute for Research and Evaluation, Chapel Hill, NC, USA. ringwalt@pire.org
Abstract:
Investigators have used both one- and two-tailed tests to determine the significance of findings yielded by program evaluations. While the literature that addresses the appropriate use of each type of significance test should be used is historically inconsistent, almost all authorities now agree that one-tailed tests are rarely (if ever) appropriate. A review of 85 published evaluations of school-based drug prevention curricula specified on the National Registry of Effective Programs and Practices revealed that 20% employed one-tailed tests and, within this subgroup, an additional 4% also employed two-tailed tests. The majority of publications either did not specify the type of statistical test employed or used some other criterion such as effect sizes or confidence intervals. Evaluators reported that they used one-tailed tests either because they stipulated the direction of expected findings in advance, or because prior evaluations of similar programs had yielded no negative results. The authors conclude that one-tailed tests should never be used because they introduce greater potential for Type I errors and create an uneven playing field when outcomes are compared across programs. The authors also conclude that the traditional threshold of significance that places α at .05 is arbitrary and obsolete, and that evaluators should consistently report the exact p values they find.
Related Concept Videos
Comparing Experimental Results: Student's t-Test
Types of Hypothesis Testing
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p ≠ 0.5.
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with data...
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
Microsoft Excel: Student's t-Test
To conduct a t-test in Excel, use the T.TEST function or the "Data Analysis...
Comparing the Survival Analysis of Two or More Groups
