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A pinch of probability is worth a pound of perhaps. A quote by American humorist and cartoonist James Thurber (1894 - 1961). The quote appeared in "Such a Phrase as Drifts Through Dreams," a short story in Thurber's last book, "Lanterns and Lances", Harper Publishing, 1961. The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

This applet allows you to explore the validity of confidence intervals on a proportion with various values for sample size (N) and population proportion (Pi). After you specify N, Pi, the level of confidence, and the number of simulations you wish to perform, the applet samples data according to your specification and computes a confidence interval for each simulation. The proportion of simulations for which the confidence interval contains Pi is recorded. If the method for constructing confidence intervals is valid, then about 95% of the 95% confidence intervals should contain Pi.

This simulation applet shows groups of confidence intervals for a given alpha based on a standard normal distribution. It shows how changes in alpha affect the proportion of confidence intervals that contain the mean. An article and an alternative source for this applet can be found at http://www.amstat.org/publications/jse/v6n3/applets/confidenceinterval.html.

This section of the Engineering Statistics Handbook gives the normal probability density function as well as the standard normal distribution equations. Example graphs of the distributions are shown and a justification of the Central Limit Theorem is included.

This applet demonstrates probability as the area under the normal and the standard normal curves. Students can manipulate mean, standard deviation, and lower and upper bounds to find probabilities.

This site addresses mean, median, mode, bar graphs, pie charts, and line graphs. Each topic has multiple examples with related discussion.

This tutorial takes the learner step-by-step in applying descriptive and inferential statistics using a real world situation.

This tutorial illustrates the basic principles of the Central Limit Theorem and enhances conceptual understand of why the Central Limit Theorem is important to inferential statistics.

This comprehensive collection of calculators provides users with resources for everything from introductory statistics to advanced statistical methods. Users can search by the following categories: Dictionaries, Courses with Calculators and Applets, Courses All Inclusive, and Statistics A-Z. Users can also search by the following statistical specialties: Agriculture, ANOVA, ANCOVA, Bayesian, Economics, Employment, Health, Information & Library Science, Psychology, Reliability Modeling, Research: Marketing and Opinion, Sampling Analysis, and SAS.

This tutorial on the Two Sample t test includes its definition, assumptions, hypotheses, and results as well as tests for equal variance and graphical comparisons. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.