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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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  • 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.
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  • 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.
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  • 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
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  • 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.
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  • 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.
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  • 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.
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