Key Points Non-parametric tests are used when standard assumptions are not available. These tests don’t rely on distributions ...

This calculation can be used for hypothesis testing in statistics Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive ...

Today our goal is to cover hypothesis testing and the basic z-test, as these are fundamental to understanding how the t-test works. We’ll return to the t-test soon — with real data.

Having the Kruskal-Wallis test as part of your toolbox is essential when the ANOVA test does not apply. After the Kruskal-Wallis test, you have several options when it comes to post hoc tests.

Table 1: Summary of the four possible outcomes for a hypothesis test of a difference. Other common post-hoc tests include the following: Tukey’s test – a common post-hoc test that makes adjustments to ...

The Kruskal–Wallis test is a statistical test used to compare two or more groups for a continuous or discrete variable. It is a non-parametric test, meaning that it assumes no particular distribution ...

Statistical tests require multiple data points because the tests assess variance in the observations from a study.The reason for using statistics is to see whether the variance in those ...

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Statistical significance is used to gauge the likelihood that a relationship exists between two variables, based on observational data. Contrary to popular misconception, this does not measure the ...