This site discusses the issues of reliability and vailidity as related to research.
This site has a wide collection of statistical resources inluding an online textbook covering first-year non-calculus based statistics (e.g. Normal distribution, ANOVA, Chi-Square), a simulation/demonstration section containing Java Applets on these first-year topics (ANOVA, Binomial Distribution,Central Limit Theorem, Chi Square, Confidence Interval, Correlation, Central Tendency, Effect Size, Goodness of Fit, Histogram, Normal Distribution, Power, Regression, Repeated Measures, Restriction of Range, Sampling Distribution, Skew, t-test, Transformations), and case studies covering the topics in the first-year statistics course. There is also a page with some basic statistical analysis tools that will aid in doing the computations if you have a Java enabled browser. The source code for these resources can also be downloaded from this site.
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.
Calculates unweighted kappa and kappa with linear and quadratic weightings, along with some other measures of concordance.
This page will perform an analysis of variance for the situation where there are three independent variables, A, B, and C, each with two levels. The user may enter data directly or copy and paste from a spreadsheet or other application.
This page will compute the Two-Way Factorial ANOVA for Independent Samples, for up to four rows by four columns. This page will also calculate the critical values of Tukey's HSD for purposes of post-ANOVA comparisons.
Given a sample of N values of X randomly drawn from a normally distributed population, this page will calculate the .95 and .99 confidence intervals (CI) for the estimated mean of the population.
This page will calculate the intercorrelations (r and r2) for up to five variables, designated as A, B, C, D, and E.