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. Allows for import of raw data from a spreadsheet; for samples of any size, large or small.
This page will calculate r_s , the Spearman rank- order correlation coefficient, for a bivariate set of paired XY rankings. As the page opens, you will be prompted to enter the number of items for which there are paired rankings. If you are starting out with raw (unranked) data, the necessary rank-ordering will be performed automatically.
In the Latin Square computational pages on this site, the third IV, with levels designated as A, B, C, etc., is listed as the "treatment" variable. The analysis of variance within an orthogonal Latin Square results in three F-ratios: one for the row variable, one for the column variable, and one for the third IV whose j levels are distributed orthogonally among the cells of the rows x columns matrix.
In the Latin Square computational pages on this site, the third IV, with levels designated as A, B, C, etc., is listed as the "treatment" variable. The analysis of variance within an orthogonal Latin Square results in three F-ratios: one for the row variable, one for the column variable, and one for the third IV whose j levels are distributed orthogonally among the cells of the rows x columns matrix.
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.
This page will calculate the intercorrelations (r and r2) for up to five variables, designated as A, B, C, D, and E.
This page will calculate the intercorrelations (r) for any number of variables (V1, V2, V3, etc.) and for any number of observations per variable.
This resource defines a pie chart. It also allows the user to input values to create their own graphs. The user has control over the title, up to 15 slices, the color of each slice, and can choose a 3-D option.