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  • This site gives a definition and an example of normal distributions. Topics include assessing normality and normal probability plots.
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  • This site gives an explanation, a definition and an example of mean and variance of random variables. Definitions and properties are also included.
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  • This online, interactive lesson on special distributions provides examples, exercises, and applets covering normal, gamma, chi-square, student t, F, bivariate normal, multivariate normal, beta, weibull, zeta, pareto, logistic, lognormal, and extreme value distributions.
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  • The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.
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  • This page generates a graph of the Chi-Square distribution and displays the associated probabilities. Users enter the degrees of freedom (between 1 and 20, inclusive) upon opening the page.

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  • The page displays the sampling distribution and the standard error of the difference between two sample means. To calculate standard error, enter the standard deviation of the source population, along with the sample sizes, Na and Nb, and then click "Calculate".

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  • The third chapter of an online Introduction to Biostatistics course. Lecture notes are provided. Additionally, links for additional reading and exercises with solutions are provided.

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  • The ninth chapter of an online Introduction to Biostatistics course. Lecture notes and links for futher reading are provided.
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  • The sixth chapter of an online Introduction to Biostatistics course. Three sets of lecture notes are provided (only the first one works). Additionally, links for additional reading and exercises with solutions are provided.

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  • This resource provides two sets of detailed notes on the Bernoulli and Binomial distributions. Additional readings, examples, exercises, and links to applets illustrating the respective distributions are also given.

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