Resource Library

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 page contains applets and data files that supplement the text "Investigating Statistical Concepts, Applications, And Methods." The applets and files are organized according to chapter; each data file is available in Minitab or text format.

This applet allows users to play several probability games like Monty Hall, Gambler's Ruin, Galton's Board, etc. Select a game from the drop down menu and click "About" to read its background. Users can manipulate the parameters for each game. Graphs of the theoretical and empirical distributions are shown. Requires JAVA.

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 applet generates a histogram for two provided datasets, or by clicking "Edit Data", users can input their own data. Users can also manipulate the axes and bin width.

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.

This applet generates dotplots for different data sets and allows users to guess the location of various measures of center and spread. Clicking "Resample" produces a dotplot of random data generated by the applet. A dotplot of user-input data can be generated by clicking "Edit Data" and typing or copy and pasting the data in the textbox. To guess the mean, median, standard deviation, and interquartile range (IQR) users check the "Guess Mean/Median", "Guess Deviation", or "Guess IQR" box and slide the relevant marker along the horizontal axis. When "Guess Deviation" is selected, users can also select "Show Percentages" to display the percentage of data points within the user's current guess for standard deviation. Clicking "Show Actual" displays the actual position of the selected measure on the dotplot. Clicking on an individual data point shows its value. Users can edit the data under "Edit Data" or by clicking and dragging the data points on the graph.

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 applet shows a scatterplot of height versus foot length. Users can add or delete points and then guess the regression line by clicking "Your Line" and moving the blue regression line. By clicking "Regression Line" users can see the actual regression line. The applet also shows the correlation and R-square for the data as well as the residuals and squared residuals for the guessed regression line and the actual regression line.

The textbook for this course discusses cross-cultural variations in household structure, as well as changes across time in household structure in the United States. The purpose of this exercise is to examine variations in household structure in the United States according to race and historical period. By the end of the exercise students should have a better appreciation of the fact that household structure in the U.S. is very fluid and that changes over time in household structure have not progressed uniformly for all race groups.