Resource Library

This source defines and explains variance and standard deviation.

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

Part of an online statistics textbook. Topics include: (1) Law of Large Numbers for Discrete Random Variables, (2) Chebyshev Inequality, (3) Law of Averages, (4) Law of Large Numbers for Continuous Random Variables, (5) Monte Carlo Method. There are several examples and exercises that accompany the material.

This resource provides the user with a formula for obtaining sample sizes of a mean and proportion.

This article may help the user understand the concept of statistical significance and the meaning of the numbers produced by The Survey System. This article is presented in two parts. The first part simplifies the concept of statistical significance as much as possible; so that non-technical readers can use the concept to help make decisions based on their data. The second part provides more technical readers with a fuller discussion of the exact meaning of statistical significance numbers.

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".

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

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

A small collection of applets on the following topics: Introduction to Probability Models, Hypergeometric Distribution, Poisson Distribution, Normal Distribution, Proportions, Confidence Intervals for Means, The Central Limit Theorem, Bivariate Normal Distribution, Linear Regression, Buffon's Needle Problem.