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

You then run statistical tests on your observations.You use the standard in psychology for statistical testing that allows a 5 percent chance of getting a false positive result.

A t-test is an inferential statistic used in hypothesis testing to determine if there is a statistically significant difference between the means of two samples.

Statistical significance is a result that’s not likely to occur randomly and is likely traceable to an identifiable prompt.

In this article, we review the function of post-hoc tests in statistical analysis, how to interpret them and when to use them (and not use them).

A recent Supreme Court ruling sheds light on the limits of statistical significance.

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.

The following section discusses the statistical tests performed in the MULTTEST procedure. For continuous data, a t-test for the mean is available. For discrete variables, available tests are the ...

This claim about statistics is nonsense. After all, statistical tests are merely a tool. Just as a gun can neither secure dinner in the woods nor injure a person in a bank until someone pulls the ...