Probability

The generation of random numbers is too important to be left to chance. The title of a 1969 article by American Mathematician and civil rights activist Robert R. Coveyou (1915 - 1996). ("Appl. Math.," 3 p. 70-111)

A cartoon to teach about proper reporting of statistical results such as conclusions from a significance test. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

This activity represents a very general demonstration of the effects of the Central Limit Theorem (CLT). The activity is based on the SOCR Sampling Distribution CLT Experiment. This experiment builds upon a RVLS CLT applet (http://www.ruf.rice.edu/~lane/stat_sim/sampling_dist/) by extending the applet functionality and providing the capability of sampling from any SOCR Distribution. Goals of this activity: provide intuitive notion of sampling from any process with a well-defined distribution; motivate and facilitate learning of the central limit theorem; empirically validate that sample-averages of random observations (most processes) follow approximately normal distribution; empirically demonstrate that the sample-average is special and other sample statistics (e.g., median, variance, range, etc.) generally do not have distributions that are normal; illustrate that the expectation of the sample-average equals the population mean (and the sample-average is typically a good measure of centrality for a population/process); show that the variation of the sample average rapidly decreases as the sample size increases.

This activity will allow students to familiarize themselves with technology and its use in calculating marginal, conditional, and joint distributions, as well as making conclusions from these tabular and graphical displays. The corresponding data set 'Pizza Data' is located at the following web address: http://www.causeweb.org/repository/ACT/PIZZA.TXT