a very general Student t-test web page -- paired or unpaired, equal- or unequal-variance, from individual observations (which can be key-entered or copy/pasted) or summary data (N, Mean, SD or SEM). Includes explanations and advice on carrying out this type of test.
Paired Student t Test -- on up to 42 pairs of values, along with a postulated population mean difference.
Testing Two Populations -- Unpaired Student t test for up to 80 observations in each sample. Also accepts a postulated difference between the two population means, which can be different from 0.
Very general n-way factorial ANOVA, with interactions, means table, interaction plots, Bonferroni post-hoc multiple comparisons, and confidence intervals. (When you get to the Rweb page, scroll down to the Analysis Menu and select ANOVA.)
Repeated-Measures ANOVA for correlated samples (extension of paired Student t-test to more than 2 matched measurements)...
Post-hoc Tests -- After doing a two-way (or other) ANOVA, post -hoc tests (also called post tests) compare individual pairs of groups. This calculator does not perform the ANOVA calculations, but takes the output from an ANOVA (residual means square error, degrees of freedom) performs a post-hoc test between any pairs of cells that you select (using cell means and N's), at whatever alpha you specify.
K-S Test for Equality of Two Populations -- Given two sets of frequencies (using the same grouping intervals), this page calculates the Kolmogorov-Smirnov test.
Kruskal-Wallis test (non-parametric ANOVA) for 2 or more groups of unpaired data -- This page requires that you first cross-tabulate your data into a matrix, with a row for every group and a column for every different numeric value that any subject had; the cell of the matrix tell how many subjects (if any) in that group had exactly that numeric value.
Paired Preferences Test -- Enter the sample size, and the two percentages (preferring A and preferring B), and this program will calculate the T score and significance level. This page is based on a normal approximation to the binomial distribution, and should not be used if the sample size is less than 30.
Sequential Analysis -- each subject's data (usually paired comparisons) is tested as it becomes available, and a decision is made to accept or to reject the null hypothesis or to keep testing.
by Paired Preferences -- Each pair of observations is compared and rated qualitatively as "preferring A" or "preferring B"
WebStat (an integrated (Java) applet) can perform Z-tests and T-tests (one- and two-sample) for population means, and Chi-square and Fisher-F tests for population variances
