Regression

  • This collection of tutorials demonstrates various statistical topics with data and provides SPSS and Minitab code. Topics covered: Measures of Central Tendency; Sign Test; Chi-Square; Mann-Whitney Test; Wilcoxon Matched-Pairs Signed-Ranks Test; Kruskal-Wallis One-Way Analysis of Variance; Friedman Two-Way Analysis of Variance; Spearman Rank Correlation; Pearson Product-Moment Correlation; Multiple Regression; t-Test for Independent Samples; t-Test for Matched Pairs; One-Way ANOVA; Two-Way ANOVA.
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  • This article introduces Radial Basis Function (RBF) networks. These networks rely heavily on regression analysis techniques. Topics include Nonparametric Regression, Classification and Time Series Prediction, Linear Models, Least Squares, Model Selection Criteria, Ridge Regression, and Forward Selection.
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  • These pages from the University of Melbourne explain statistical concepts using various examples from medicine, science, sports, and finance. The intent is not computational skill but conceptual understanding. Some pages also contain data.
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  • This applet allows users to draw a curve on a graph, and then displays the polynomial fit of the curve.
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  • This collection of datasets addresses social science issues and is housed at the University of Wisconsin. Free registration is required to access the datasets.
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  • This random number service allows users to generate up to 10,000 random integers with duplicates, randomized sequences without duplicates, or up to 16 kilobytes of raw random bytes. Users can also flip virtual coins and generate random bitmaps. Key word: Random Number Generator.

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  • HotBits is a genuine random number generator powered by radioactive decay. Simply click the "Request HotBits" link, and specify how many bytes you would like (up to 2048) and in what form you prefer them. Hexadecimal returns numbers and letters, while C language returns integers. Then click the "Get HotBits" button, and your random numbers will appear on the screen.
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  • This page explains simple linear regression with an example on muscle strength versus lean body mass.
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  • This lesson introduces simple linear regression with several Excel spreadsheet examples such as temperature versus cricket chirps, height versus shoe size, and laziness versus amount of TV watched. These activities require class participation.
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  • This online calculator allows users to enter 16 observations with up to 4 dependent variables and calculates the regression equation, the fitted values, R-Squared, the F-Statistic, mean, variance, first order serial-correlation, second order serial-correlation, the Durbin-Watson statistic, and the mean absolute errors. It also tests normality and gives the i-th residuals.

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