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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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  • SalStat is an small application for the statistical analysis of scientific data (with a special concentration on psychology). It can already do 18 kinds of descriptive statistics, t tests (paired, unpaired and one sample), 3 kinds of correlations linear regression and point biserial tests, and single factor ANOVA (both within and between subjects). Data are entered on an easy-to-use datagrid like a spreadsheet, and all the analyses are driven by menus and dialog boxes. Output can be formatted to HTML.

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  • MacAnova is a free, noncommercial, interactive statistical analysis program for Windows 95/98/NT, Windows 3.1 with Win32s, Macintosh and Unix. MacAnova has many capabilities but its strengths are analysis of variance and related models, matrix algebra, time series analysis (time and frequency domain), and (to a lesser extent) uni-variate and multi-variate exploratory statistics.
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  • Lisp-Stat is an extensible statistical computing environment for data analysis, statistical instruction and research, with an emphasis on providing a framework for exploring the use of dynamic graphical methods. The object-oriented programming system is also used as the basis for statistical model representations, such as linear and nonlinear regression models and generalized linear models. Many aspects of the system design were motivated by the S language.
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  • ViSta constructs very-high-interaction, dynamic graphics that show you multiple views of your data simultaneously. The graphics are designed to augment your visual intuition so that you can better understand your data.

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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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  • The applets in this section allow you to see how the common Xbar control chart is constructed with known variance. The Xbar chart is constructed by collecting a sample of size n at different times t. The process is considered to be out of control if the sample mean of the current sample falls above or below the control limits. The user has the options to change each parameter individually and all at once. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/ControlCharts.html
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  • The applets in this section demonstrate basic issues of experimental design. The Poor Experimental Design ignores randomization rules and allows for increased experimental error. The Improved Experimental Design offers improvement over the first design by adding randomization and reducing experimental error. Both applets require the input of several participants. The purpose of the applets is to test the reaction times between a participant's dominant and non-dominant hand. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/ExpDesign.html
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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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