This page will compute the t-test for either correlated or independent samples. One may copy and paste data in or type the data in individually.
This page will compute the t-test for either correlated or independent samples. One may copy and paste data in or type the data in individually.
These pages will perform an analysis of covariance for k independent samples, where the individual samples, A, B, etc., represent k quantitative or categorical levels of the independent variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. The pages in this first batch require the direct entry of data, item by item, and as they open you will be prompted to enter the size of the largest of your several samples. The pages in this second batch allow for the import of data from a spreadsheet via copy and paste procedures.
These pages will perform a factorial analysis of covariance for RxC independent samples, cross-tabulated according to two independent variables, A and B, where A is the row variable and B the column variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. As the pages open, you will be prompted to enter the size of the largest of your several samples.
Generate a graphic and numerical display of the properties of the Normal Distribution. For a unit normal distribution, with M=0 and SD=α1, enter 0 and 1 at the prompt. For a distribution with M=100 and SD=α15, enter 100 and 15. And so forth
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.
Given three overlapping correlation coefficients: rXY, rXZ, and rYZ, this page will calculate the first-order partial correlations: rXY.Z, rXZ.Y, and rYZ.X. If you enter the value of N (providing N>6), the program will also calculate the values of t for the partial correlations (df=N-3) along with the associated two-tailed probability values.
This page will calculate the first- and second-order partial correlations for four intercorrelated variables, W, X, Y, and Z. If you enter a value of N (providing N>9), the program will also calculate the values of t along with the associated two-tailed probability values.
This page will calculate the value of chi-square for a one- dimensional "goodness of fit" test, for up to 8 mutually exclusive categories labeled A through H. To enter an observed cell frequency, click the cursor into the appropriate cell, then type in the value. Expected values can be entered as either frequencies or proportions. Toward the bottom of the page is an option for estimating the relevant probability via Monte Carlo simulation of the multinomial sampling distribution.
For a situation in which independent binomial events are randomly sampled in sequence, this page will calculate (a) the probability that you will end up with exactly k instances of the outcome in question, with the final (kth) instance occurring on trial N; and (b) the probability that you will have to sample at least N events before finding the kth instance of the outcome.
Log-linear analysis is a version of chi-square analysis in which the relevant values are calculated by way of weighted natural logarithms. This page will calculate several values of G^2.