A slideshow presentation with two good examples on using the Z-test for the difference between two means. Gives some good "plain language" interepretations of what "statistically significant difference" means.
This particular textbook lesson addresses the independent t-test. It presents to the user how to compute the t statistic and then how to interpret the results.
This page gives a short background on Student's t-test and provides three t-test calculators. Two perform t-tests for independent groups and one performs t-tests for matched pairs. Users type in individual data points or copy and paste the entire data set. Some examples are given for demonstration.
Gives textbook-like explanation with some real-life data to compute a t-test and determine if two population means are equal. Also has some links for case studies and a web-based program called Dataplot. There is a printer-friendly version on the main homepage (see source).
Gives very detailed explanation of t-tests (confidence intervals, one-sample, two sample independent, two sample paired, pooled and unpooled variances). Discusses the assumptions that are made for each type of t-test. This topic is part of an online textbook.
Gives four practice problems on the t-test. Gives both the data sets and the mean and standard deviations if you did not want to compute them. Requires students to interpret and reason through some of their answers.
The Against All Odds video series provides an extensive introduction to statistics. It consists of 26 half hour video episodes that include lecturing on statistical topics, animations of statistical topics and video of real world examples. The series is available online or can be purchased on VHS video tape. The statistical material in the series was supervised by Dr. David Moore and accordingly much of the material echos the language used in Moore's textbooks. Topics covered include most topics from an introductory statistics course and slightly more advanced topics such as seasonal variation, blocking of experimental designs and even Chernof faces. The material is very well suited for students in undergraduate statistics classes.