• ### Internal Validity Tutorial

This tutorial introduces 9 sources of threat to internal vailidity and asks the user to classify hypothetical experiments as either internally valid or invalid and identify the source of threat if invalid.
• ### HyperStat Online: Ch. 6 Sampling Distributions

This chapter of the HyperStat Online Textbook discusses in detail sampling distributions of various statistics (mean, median, proportions, correlation, etc.), differences between such statistics, the Central Limit Theorem, and standard error, giving formulas, examples, and exercises.

• ### Rice Virtual Lab in Statistics

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.

• ### Simulation of the t-distribution

The t-distribution activity is a student-based in-class activity to illustrate the conceptual reason for the t-distribution. Students use TI-83/84 calculators to conduct a simulation of random samples. The students calculate standard scores with both the population standard deviation and the sample standard deviation. The resulting values are pooled over the entire class to give the simulation a reasonable number of iterations.
• ### Sampling Distributions (Presentation 7)

This PowerPoint presentation teaches sampling distributions related to proportions and means using multiple examples, charts, and graphs.
• ### Analysis Tool: Log-Linear Analysis for an AxBxC Contingency Table

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.

• ### Analysis Tool: Kappa as a Measure of Concordance in Categorical Sorting

Calculates unweighted kappa and kappa with linear and quadratic weightings, along with some other measures of concordance.

• ### Analysis Tool: 2x2x2 Analysis of Variance for Independent Samples

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.

• ### Analysis Tool: One-Way Analysis of Variance for Independent or Correlated Samples

This page will compute the One-Way ANOVA for up to five samples. The design can be either for independent samples or correlated samples (repeated measures or randomized blocks). This page will also perform pair-wise comparisons of sample means via the Tukey HSD test

• ### Analysis Tool: Two-Factor ANOVA with Repeated Measures on Both Factors

This page will perform a two-way factorial analysis of variance for designs in which there are 2-4 levels of each of two variables, A and B, with each subject measured under each of the AxB combinations.