Resource Library

This applet introduces the concept of confidence intervals. Select an alpha level, sample size, and the number of experiments, and click "Play." For each sample, the applet will show the data points as blue dots and the confidence interval as a red, vertical line. The true population mean is shown as a horizontal purple line, and green ovals indicate which intervals do not contain the true mean.

This page provides links to distribution calculators, conceptual demonstration applets, statistical tables, online data analysis packages, function and image-processing tools, and other online computing resources. Key Words: Binomial; Normal; Exponential; Chi-Square; Geometric; Hypergeometric; Negative Binomial; Poisson; Student's T; F-Distribution; Wilcoxon Rank-Sum; Central Limit Theorem; Regression; Normal Approximation to Poisson; Confidence Intervals; Hypothesis Tests; Power; Sample-Size; ANOVA; Galton's Board; Function Plots; Edge Detection; Image Warping & Stretching; Polynomial Model Fitting; Wilcoxon-Mann-Whitney Statistic.

This collection of datasets covers many application areas, but are all for time series analysis. The data are in text format.

In this module you will have the opportunity to explore the frequency of different types of residential moves carried out by Americans. You will examine some of the basic determinants of residential mobility by looking at variations in different types of mobility by age, marital status, education, and housing tenure. Finally, you will have an opportunity to test hypotheses, drawn from a popular theoretical perspective, about racial differences in residential mobility.

In this module you will explore some of the impacts of this immigration by examining the characteristics of the foreign-born population, comparing these characteristics to those of the native born population. You will get a chance to explore where immigrants come from, how the composition of the immigrant population has changed, where immigrants settle, and what they do once they get here. Most importantly, you will have the opportunity to test some key hypotheses drawn from the most popular theory used to explain the incorporation of immigrants into the American social and economic mainstream.

As discussed, the murder rates for Blacks in the United States are substantially higher than those for Whites, with Latino murder rates falling in the middle. These differences have existed throughout the 20th and into the 21st century and, with few exceptions, are found in different sections of the United States. Although biological and genetic explanations for racial differences in crime rates, including murder, have been discredited and are no longer accepted by most criminologists, both cultural and structural theories are widespread in the literature on crime and violence. It is also important to remember that Latino is an ethnic rather than a racial classification. The point of this exercise is to examine differences in selected structural positions of Blacks, Whites and Latinos in the United States that may help explain long-standing differences in their murder rates.

This tutorial provides a basic introduction to many topics in statistics and probability. Topics include: Sets and subsets, Statistical experiments, Counting, Basic probability rules, Bayes' theorem, Probability distributions, Discrete vs. Continuous, Binomial, Negative Binomial, Hypergeometric, Multinomial, Poisson, Normal, Sampling theory, Central tendency, Variability, Sampling distributions, t Distribution, Chi-Square Distribution, F Distribution, Estimation problems, Hypothesis testing, Power, Survey sampling, Simple random samples, Stratified samples, Cluster samples, Sample size.

The datasets in this collection are in text format, but are also compatible with Arc software from "Regression Graphics." Each set has a title, description, and data table. The software is available in the relation link below.

This resource explains Multiple Regression and concepts associated with it. Key Words: Predicted values; Residuals; Dummy Variables; Interaction Effects; T-Test; Regression Coefficients; Correlation; Partial Correlation; R-Squared; Adjusted R-Squared; Multicollinearity; Variance-Inflation Factors; Transformation; Cook's Distance; Validity; Durbin-Watson Coefficient.

This lesson introduces simple linear regression with several Excel spreadsheet examples such as temperature versus cricket chirps, height versus shoe size, and laziness versus amount of TV watched. These activities require class participation.