This lesson involves investigating chi-squared tests and distributions.

This lesson involves deriving and interpreting the chi-square as an indication of whether two variables in a population are independent or associated.

This activity involves investigating whether a difference really seems to exist between two sample means.

In this lesson, samples are generated from a population for a particular hypothesis test, leading to the conjecture that the null hypothesis is actually false.

This lesson involves approximate sampling distributions obtained from simulations based directly on a single sample. The focus of the lesson is on conducting hypothesis tests in situations for which the conditions of more traditional methods are not met.

This activity allows students to experiment with different alpha levels and alternative hypotheses to investigate the relationship among types of error and power.

This lesson involves beginning with a null hypothesis specifying the mean of a normally distributed population with a given standard deviation.