Javascript

  • Generate a graphic and numerical display of the properties of the F-Distributions, for any value of df_numerator and for values of df_denominator >= 5.

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  • This page performs a Kolmogorov-Smirnov "Goodness of Fit" test for categorical data. Users enter observed frequencies and expected frequencies for up to 8 mutually exclusive categories. The applet returns the critical values for the .05 and .01 levels of significance.

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  • Given the population incidence of a certain disease, and the conditional probabilities of positive and negative test results, what are the probabilities for a particular test result of a true positive, true negative, false positive, and false negative? Adaptable to other kinds of conditional situations. Although this page is adaptable to a variety of backward probability situations, its exemplary case is the one in which one is seeking to make sense of the result of a medical test.

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  • A paper discussing the development of construct validity as applied to psychological studies.
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  • This chapter of the "Concepts and Applications of Inferential Statistics" online textbook describes in detail the Kruskal-Wallis test, it's formulas, variables, and procedures using an example involving wine-tasters.

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  • Explains how to set up the Kruskal-Wallis test and gives the formula for the test statistic.
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  • The page calculates summary statistics for any dataset. Users will be prompted for sample size when opening this page. The calculator returns mean, sum of X, sum of X^2, variance, standard deviation, and standard error. Key word: Descriptive statistics.

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  • To perform calculations using Bayes' theorem, enter the probability for one or the other of the items in each of the following pairs (the remaining item in each pair will be calculated automatically). A probability value can be entered as either a decimal fraction such as .25 or a common fraction such as 1/4

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  • An application of Bayes Theorem that performs the same calculations for the situation where the several probabilities are constructed as indices of subjective confidence.

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  • This page will perform basic multiple regression analysis for the case where there are several independent predictor variables, X1, X2, etc., and one dependent or criterion variable, Y. Requires import of data from a spreadsheet.

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