T test as a parametric statistic [PDF]
Korean Journal of Anesthesiology, 2015 In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n).
Tae Kyun Kim
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A simple guide to the use of Student’s t-test, Mann-Whitney U test, Chi-squared test, and Kruskal-Wallis test in biostatistics [PDF]
BioData MiningIn an age when machine learning and artificial intelligence are broadly employed, traditional statistics can still provide insightful information and results quickly and at a low computational cost.
Davide Chicco +2 more
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Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. [PDF]
Neuron, 2022 In basic neuroscience research, data are often clustered or collected with repeated measures, hence correlated. The most widely used methods such as t-test and ANOVA do not take data dependence into account, and thus are often misused.
Yu Z +5 more
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A tutorial on using the paired t test for power calculations in repeated measures ANOVA with interactions. [PDF]
Behav Res Methods, 2023 The a priori calculation of statistical power has become common practice in behavioral and social sciences to calculate the necessary sample size for detecting an expected effect size with a certain probability (i.e., power).
Langenberg B +4 more
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Attach importance of the bootstrap t test against Student's t test in clinical epidemiology: a demonstrative comparison using COVID-19 as an example. [PDF]
Epidemiol Infect, 2021 Student's t test is valid for statistical inference under the normality assumption or asymptotically. By contrast, although the bootstrap t test was proposed in 1993, it is seldom adopted in medical research.
Zhao S +7 more
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Correction: Why Psychologists Should by Default Use Welch’s 't'-test Instead of Student’s 't'-test
International Review of Social Psychology, 2022 This article details a correction to: Delacre, M., Lakens, D., & Leys, C. (2017). Why Psychologists Should by Default Use Welch’s 't'-test Instead of Student’s t-test. 'International Review of Social Psychology', 30(1), 92–101.
Marie Delacre +2 more
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Application of student's t-test, analysis of variance, and covariance. [PDF]
Ann Card Anaesth, 2019 Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups.
Mishra P +4 more
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More about the basic assumptions of t-test: normality and sample size. [PDF]
Korean J Anesthesiol, 2019 Most parametric tests start with the basic assumption on the distribution of populations. The conditions required to conduct the t-test include the measured values in ratio scale or interval scale, simple random extraction, normal distribution of data ...
Kim TK, Park JH.
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Analysis of Bayesian posterior significance and effect size indices for the two-sample t-test to support reproducible medical research. [PDF]
BMC Med Res Methodol, 2020 Background The replication crisis hit the medical sciences about a decade ago, but today still most of the flaws inherent in null hypothesis significance testing (NHST) have not been solved.
Kelter R.
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Why Psychologists Should by Default Use Welch’s t-test Instead of Student’s t-test
International Review of Social Psychology, 2017 When comparing two independent groups, psychology researchers commonly use Student’s 't'-tests. Assumptions of normality and homogeneity of variance underlie this test.
Marie Delacre +2 more
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