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  • 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.
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  • This online calculator allows users to enter 16 observations with up to 4 dependent variables and calculates the regression equation, the fitted values, R-Squared, the F-Statistic, mean, variance, first order serial-correlation, second order serial-correlation, the Durbin-Watson statistic, and the mean absolute errors. It also tests normality and gives the i-th residuals.

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