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  • This site explains the relationship between hypothesis testing and confidence intervals.
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  • This page discusses the understanding of and interpretation of p-values for those who read articles with statistical information.
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  • This resource briefly explains what a significance level is and how they are used in hypothesis testing. It also includes other links related to significance level such as "Type I error" and "significance test".
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  • This article may help the user understand the concept of statistical significance and the meaning of the numbers produced by The Survey System. This article is presented in two parts. The first part simplifies the concept of statistical significance as much as possible; so that non-technical readers can use the concept to help make decisions based on their data. The second part provides more technical readers with a fuller discussion of the exact meaning of statistical significance numbers.
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  • This resource provides the user with a formula for obtaining sample sizes of a mean and proportion.
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  • This resource assists the user in reading, constructing, and understanding confidence intervals.
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  • Students can sample numerous bags of M&Ms. A plot of the relative frequency of each color is continually updated above the sampling frame. Each sample bag of M&Ms contains 56 candies.
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  • This applet simulates families of three children. The probability of having a boy on any attempt can be changed in the parameter statement. The percantage of times "x" number of girls occurs is updated in the bar chart. There is a 2nd applet on the page that is the same as above, but the families stop having children after the first boy or after they have had 3 girls.
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  • Part of an online statistics textbook. Topics include: (1) Law of Large Numbers for Discrete Random Variables, (2) Chebyshev Inequality, (3) Law of Averages, (4) Law of Large Numbers for Continuous Random Variables, (5) Monte Carlo Method. There are several examples and exercises that accompany the material.
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  • This lesson on the Poisson distribution explains the theory, history, and applications of the distribution and gives examples and a multiple choice test.
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