Learn how two-tailed tests determine statistical significance in hypothesis testing by evaluating if a sample differs from a population mean. Discover real-world applications.

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 t test is a commonly used hypothesis test in statistics that allows us to compare the mean value of a group of sampled data with some hypothesized value, usually a population mean value (from the ...

Significance testing was developed as an objective method for summarizing statistical evidence for a hypothesis. It has been widely adopted in genetic studies, including genome-wide association ...

A statistical hypothesis test for a difference between the spatial distributions of two populations is presented. The test is based upon a generalization of the two-sample Cramér-von Mises test for a ...