Multivariate Quantitative Relationships

  • This program visualizes the effects of outliers to regression lines. The user may pick up a point with the mouse and move it across the chart. The resulting regression line is automatically adjusted after each movement, showing the effect in an immediate and impressive way. The program Leverage allows one to experiment with the leverage effect. You can create a random sample of data noisy points on a line. Dragging one of the points away from the regression line immediately shows the effect, as the regression line is recalculated and moves according to the current data set. Not online: user has to download the program.

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  • This program has been written to explore the relationship between the data points and the error surface of the regression problem. On one hand you can learn how to represent a line in two different spaces ({x,y} and {k,d}), and on the other hand you see that solving the regression problem is nothing else than finding the minimum in the error surface.

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  • The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1. The Creation applet allows the user to create a data set by adding or deleting points from the screen. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/Correlation.html
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  • Each dataset in this collection includes description of the study, description of the data file, statistical topic covered, and reference. Topics addressed include: correlation, one-way ANOVA, Bonferroni multiple comparison procedure, regression (simple, multiple, and loglinear), chi-square, and the t-test.
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  • This page is a collection of examples, demonstrations, and exercises that can be used to motivate a lecture, demonstrate an important point, or create a laboratory exercise for students. Topics include the following: Descriptives, Normal Distribution, Sampling Distributions, Probability, Chi-Square, t tests, Power, Correlation/Regression, One-way Anova, Multiple Comparisons, Factorial Anova, Repeated Measures, Multiple Regression, General Linear Model, Log Linear Models, and Distribution-Free Tests.
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  • A collection of applets addressing data analysis, sampling distribution simulations, and probability and inference. Some can be used individually, though others require context from the textbook.

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  • This page has data sets used by UCLA statistics classes. The html files in the second column contain descriptions of a particular data set and a link to the data at the end of the file. There are also .dat and .dta files that contain just data, with no description.
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  • This page discusses disadvantages of large datasets with regard to Simpson's Paradox.
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  • This page contains information and links about statistical literacy. Some links are to textbooks, online articles, resources, and information about upcoming events.
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  • This module contains discussions on t-test, ANOVA, correlation, two-way factorial ANOVA, regression, chi-squared, and distributions and provides links to a variety of activities relevant to the discussions.
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