This article describes thet-test assumptionsand provides examples of R code to check whether the assumptions are met before calculating the t-test. You will learn the assumptions of the different types of t-test, including the: one-sample t-test independent t-test paired t-test Contents: Ass...
What are the assumptions for conducting the independent samples t-test? Describe the assumptions of the two-samples t-tests. What other assumptions must be met before using either two-sample t-test? What are the assumptions underlying the proper use of the t for two-sample means? What are ...
Note 1: An independent-samples t-test can also be used to determine if there is a mean difference between two change scores (also known as gain scores). However, a one-way ANCOVA is more commonly recommended for this type of study design....
Chi-square tests may be applied to the case where X is a categor- ical variable, and an independent samples t test or Wilcoxon rank sum (Mann-Whitney) test may be applied to the case where X is a continuous variable. Whenever the null hypothesis is rejected as showing the existence of...
A two independent sample t-test with equal variances is essentially a one-way ANOVA test in disguise, and so instead of testing each sample for normality, it is correct to test the combination of the data in the two samples each with their group means subtracted, as described i...
The independent variables must consist of two related groups or matched pairs. When to use a paired t-test? Paired t-tests are used when the same item or group is tested twice, which is known as a repeated measures t-test. Some examples of instances for which a paired t...
Independent, Gaussian-distributed innovations Constancy of the innovations variance within subsamples Constancy of the innovations across any structural breaks If a model violates these assumptions, then the Chow test result might not be correct, or the Chow test might lack power. Investigate whether th...
The standardStudent’s t-test(comparing two independent samples) and the ANOVA test (comparing multiple samples) assume also that the samples to be compared have equal variances. If the samples, being compared, follow normal distribution, then it’s possible to use: ...
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E.g. you could perform a two-sample t-test using the differences between the measurements at the two time periods for each subject. This will test whether there is a significant difference between the two populations from which the samples are drawn based on the change in the measurements ...