Resource Library

This applet allows the user to adjust a (1st shape) and b (2nd shape) parmaters of the Beta distribution with a slider or manual input. The applet allows the user to fix the x and or y axes. The user immediately sees how this affects the the shape of the graph as well as the variance and the expected value. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/BetaDensityApplet.html

The eighth chapter of an online Introduction to Biostatistics course. Lecture notes are provided. Additionally, links for additional reading and exercises with solutions are provided.

Gives a very brief explanation of Spearman' rho and how it differs from Pearson's r.

Teacher instructions to accompany "Markov vs. Markov" case study found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov.html.

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.