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  • The Pew Research Center For The People & The Press data archive page contains links to downloadable versions of the Center's survey data which are currently available on the web. Survey data are released six months after the reports are issued and are posted on the web as quickly as possible.
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  • This site provides links to tests and quizzes for the Statistics and Data Analysis for Public Policy and Sociology course at Duke University for 1992 through 1995.
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  • The datasets on this page are classified by analysis technique (ANOVA, Linear Regression, Markov Chain Monte Carlo, Nonlinear Regression, and Univariate Summary Statistics) and by level of difficulty (lower, average, higher). They were originally intended to test statistical software.
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  • This page introduces the definition of sufficient statistics and gives two examples of the use of factorization to prove sufficiency.
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  • This online, interactive lesson on Markov chains provides examples, exercises, and applets that cover recurrence, transience, periodicity, time reversal, as well as invariant and limiting distributions.
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  • This is a basic web application that allows practice with matching points on a scatterplot to the appropriate correlation coefficient, r. Applet provides four scatterplots to match with four numeric correlations via radio buttons. After making selections, students click to see "correct" answers and keep a running total of proportion of correct matches, then may select four more plots.
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  • Discusses the benefits of Taguchi methods applied to engineering.
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  • Discusses Markov chains, transition probabilities, and the transition probability matrix.
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  • Develops the idea of the transition matrix and what it can tell you.
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  • This case study explores statistics on divorce rates using Markov chains. Two closely related statistics are presented: the chance of divorcing in a given year and the chance of divorcing over the lifetime of a marriage. Accompanying teacher instructions are found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov_notes.html
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