Resource Library

This JAVA applet is designed to give students practice in calculating basic probabilities using the binomial distribution. The applet gives students short problem descriptions that require a binomial probability to solve. The user is then prompted to follow a step by step process to find the probability. Users must answer a step correctly before the applet will allow them to move on to the next step. The page also gives further exercises that allow the user to think about binomial distributions more deeply and gives a link to a more detailed information about the binomial distribution.

The online "Engineering Statistics Handbook" provides a section (4.6 Case Studies in Process Modeling) using detailed realistic examples from physical science and engineering applications. Examples in Load Cell Calibration, Alaska Pipeline Ultrasonic Calibration, Ultrasonic Reference Block Study, and Thermal Expansion of Copper Case Study are presented in a step-by-step manner.

This site provides case studies which cover subject areas including: analysis of variance, boxplots, confidence intervals, contrast among means, correlated t-test, correlation, histograms, independent groups t-test, regression, repeated measures ANOVA, and t-tests.

This case study explores statistics on divorce rates using Markov chains. Two closely related statistics are presented: the chance of divorcing in a given year and the chance of divorcing over the lifetime of a marriage. Accompanying teacher instructions are found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov_notes.html

This article gives a description of typical sources of error in public opinion polls. It gives a short but insightful explanation of what the margin of error indicates as well as other common errors in opinion polls.

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.

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

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.