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  • This page generates a graph of the sampling distribution of r, the Pearson correlation coefficient. Upon opening, the applet prompts for sample size greater than 6. The applet also displays the probabilities associated with the distribution.

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  • Calculates the areas under the curve of the normal distribution falling to the left of -z, to the right of +z, and between -z and +z.

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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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  • Calculates the z-ratio and associated one-tail and two-tail probabilities for the difference between two correlated proportions, such as might be found in the case where the proportions are based on the same sample of subjects or on matched samples.

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  • To assess the significance of any particular instance of r, enter the values of N[>6] and r into the designated cells, then click the 'Calculate' button. Application of this formula to any particular observed sample value of r will accordingly test the null hypothesis that the observed value comes from a population in which rho=0.

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  • This page will perform a t-test for the significance of the difference between the observed mean of a sample and a hypothetical mean of the population from which the sample is randomly drawn. The user will be asked to specify the sample size as the page opens.

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  • This calculator performs the following for a contingency table up to 5x5: chi-square analysis; Cramer's V; two asymmetrical versions of lambda; the Goodman-Kruskal index of predictive association; other measures relevant to categorical prediction. Key Word: Categorical Analysis.

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  • This page calculates the point biserial correlation coefficient for the case where one variable is dichotomous and the other is non-dichotomous. This page allows the user to input the data directly or copy and paste from a spreadsheet application and provides data summary.

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  • The following pages calculate r, r-squared, regression constants, Y residuals, and standard error of estimate for a set of N bivariate values of X and Y, and perform a t-test for the significance of the obtained value of r. Values of X and Y are entered directly into individual data cells. This page will also work with samples of any size, though it will be rather unwieldy with samples larger than about N=50. As the page opens, you will be prompted to enter the value of N.

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  • This page has two calculators. One will cacluate a simple logistic regression, while the other calculates the predicted probability and odds ratio. There is also a brief tutorial covering logistic regression using an example involving infant gestational age and breast feeding. Please note, however, that the logistic regression accomplished by this page is based on a simple, plain-vanilla empirical regression.

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