T-test, (Students t-test):  This simple statistic allows you to compare whether your data are significantly different from some expected value.  For example, you measure water temperature in Hennington pond every day at noon for the month of September to test the hypothesis that September 2000 has been significantly hotter for campus aquatic systems than past years.  Fortunately, you have access to daily water temperature data from last September, and from every September in the 1990s.  You set up your spreadsheet with 2000 data paired in rows with 1999 data, each row being the measurement from the same day in September.  A t-test will tell you whether 2000 was significantly hotter than 1999.  Replace the 1999 data with the means of daily water temperatures for each September day for the 1990s, and you can see if September 2000 has been significantly hotter than the 1990s in general.  You can also use t-tests to compare 1 dataset to another by pairing them together—this is called a paired t-test, ironically enough!

The t-test can be used to compare two sets of data and measure the amount of overlap. Students will not be expected to calculate values of t.
( The t-test should only be used on normally distributed data, ideally with large samples (>30 measurements per set of data) and the value of t should be compared with the critical value at # degrees of freedom. For sample sizes <30 the value of t is only approximate and the degrees of freedom is n1+ n2 - 2. If t > critical value then it is possible to reject the null hypothesis)