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  • R is an integrated suite of software facilities for data manipulation, calculation and graphical display. R is a free software environment and language for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

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  • The Journal of Statistics Education disseminates knowledge for the improvement of statistics education at all levels, including elementary, secondary, post-secondary, post-graduate, continuing, and workplace education. It is distributed electronically and, in accord with its broad focus, publishes articles that enhance the exchange of a diversity of interesting and useful information among educators, practitioners, and researchers around the world. The intended audience includes anyone who teaches statistics, as well as those interested in research on statistical and probabilistic reasoning. All submissions are rigorously refereed using a double-blind peer review process.
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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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  • This site gives the outlines and shows the lessons for psychology 340/341: Advanced Statistical Methods.
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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 site describes what to do with data sets instead of simply presenting theory and methods as they appear in standard textbooks. It emphasizes statistical practices.
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  • The ICPSR provides access to a large repository of social science and political data. Data sets can be constructed and downloaded for use in most popular statistical packages.
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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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