Multivariate Quantitative Relationships

  • 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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  • 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 demonstrates the Normal approximation to the Poisson Distribution. Users can set the rate, lambda (‘é), and the number of trials, n, and observe how the shape of the distribution changes. The Poisson distribution is shown in blue, and the Normal distribution is shown in red.
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  • This applet introduces the concept of confidence intervals. Select an alpha level, sample size, and the number of experiments, and click "Play." For each sample, the applet will show the data points as blue dots and the confidence interval as a red, vertical line. The true population mean is shown as a horizontal purple line, and green ovals indicate which intervals do not contain the true mean.
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  • This page helps readers know which statistcal tests are appropriate for the different types of data. Two charts display the information. A discussion of study design and sample size, as well as exercise questions with solutions are also provided.
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  • This page provides a t-table with degrees of freedom 1-30, 60, 120, and infinity and seven levels of alpha from .1 to .0005.

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  • This page provides a z-table with alpha levels from .00 to .09.

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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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