Resource Library

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.

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 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.

This applet allows users to run experiments such as Ball and Urn, Buffon's Needle, Craps, Monty Hall, and many more. Select an experiment from the drop down menu and click "About" to read its description. Then, set the parameter values. Set the sample size using the "Update" box and the number of samples using the "Stop" box. The single arrow button takes one sample and the double arrow button takes the number of samples selected. Graphs of the theoretical and empirical distributions are shown. Requires JAVA

This scatterplot lets users plot a number of demographic variables and see the log transformation of those variables for numerous countries and income groups. Users can also see the information for any year from 1975 to 2004.

This collection of datasets was compiled by the Biostatistics Department at Vanderbilt University. They come in R, S, Excel, and ASCII formats. Each also has a description in html format.

Research has shown that marital status and employment are correlates of desistance. That is, adolescents involved with crime were more likely to discontinue offending in adulthood if they were married and had a good job. Most of what criminologists know about the process of desistance from crime is based on a sample of adult males in the 1950's. There is no question that life in America has changed drastically in the past fifty years. Given the importance of examining historical change inherent in the life course perspective, it is important to determine how changes in the social structure over time impact individuals. Therefore, the goals of this data analysis exercise are to examine changes in marriage and employment over the last fifty years. The purposes are to identify the changes that have taken place, and to hypothesize how these changes may affect the process of desistance from crime today.

This module provides an activity were students will attempt to explain how each of the following variables is related to child poverty within the United States: Race, Age, Family Type, Family Size, and Immigrant Status.

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

This module is designed to illustrate the effects of selection bias on the observed relationship between premarital cohabitation and later divorce. It also serves as a review of key methodological concepts introduced in the first part of the course.