Resource Library

By changing the number of degrees of freedom in a t-distribution, students can see how the pdf changes. They also have the option of overlayng the standard normal curve so that they can see the convergence.

Explains how to set up the Kruskal-Wallis test and gives the formula for the test statistic.

This site offers an involved definition of the likelihood ratio test with examples and formulas.

This site focuses on using the LRT to compare two competing models.

This site explains small sample hypothesis testing for a normal population and hypothesis testing for a population proportion. Includes examples and exercises.

This section on Common Statistical Tests uses an example on faculty publications to show users how to perform a one-sample t test. The discussion includes one-tailed and two-tailed tests.

This exercise will help the user understand the logic and procedures of hypothesis testing. To make best use of this exercise, the user should know how to use a z table to find probabilities on a normal distribution, and how to calculate the standard error of a mean. Relevant review materials are available from the links provided. The user will need a copy of the hypothesis testing exercise (link is provided), a table for the standardized normal distribution (z), and a calculator. The user will be asked several questions and will be given feedback regarding their answers. Detailed solutions are provided, but users should try to answer the questions on their own before consulting the detailed solutions. The end of the tutorial contains some "thought" questions.

This site explains the relationship between hypothesis testing and confidence intervals.

This page discusses the understanding of and interpretation of p-values for those who read articles with statistical information.

This resource briefly explains what a significance level is and how they are used in hypothesis testing. It also includes other links related to significance level such as "Type I error" and "significance test".