Random Variables

  • This is an e-book tutorial for R. It is organized according to the topics usually taught in an Introductory Statistics course. Topics include: Qualitative Data; Quantitative Data; Numerical Measures; Probability Distributions; Interval Estimation; Hypothesis Testing; Type II Error; Inference about Two Populations; Goodness of Fit; Analysis of Variance; Non-parametric methods; Linear Regression; and Logistic Regression.
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  • BrightStat is a free online application for statistical analyses. Besides many non-parametric tests, BrightStat offers multiple linear regression, logistic regression, ANOVA and repeated measurements ANOVA as well as Kaplan Meier Survival analysis. BrightStat has an easy to use GUI and supports the creation of mostly used scientifc graphs such as line-, bar-, scatter- and box-plots as well as histograms.

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  • The International Statistical Literacy Project (ISLP) puts out a newsletter bimonthly. According to ISLP, "The mission of the International Statistical Literacy Project (ISLP) is to support, create and participate in statistical literacy activities and promotion around the world." This newsletter is a way to get information out to those interested.
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  • A cartoon to teach about the interpretation of confidence statements. The cartoon plays on the idea of what would happen if the same process was repeated over-and-over again. 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.

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  • This hands-on activity is appropriate for a lab or discussion section for an introductory statistics class, with 8 to 40 students. Each student performs a binomial experiment and computes a confidence interval for the true binomial probability. Teams of four students combine their results into one confidence interval, then the entire class combines results into one confidence interval. Results are displayed graphically on an overhead transparency, much like confidence intervals would be displayed in a meta-analysis. Results are discussed and generalized to larger issues about estimating binomial proportions/probabilities.
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  • In the fields of observation chance favors only the prepared mind. A quote from French chemist and microbiologist Louis Pasteur (1822 - 1895) given at a lecture at University of Lille on December 7, 1854.

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  • A cartoon to teach about the family of t-distributions including their relationship to the normal distribution. Cartoon by John Landers (www.landers.co.uk) based on an idea and sketch from Sheila O. Weaver (University of Vermont). This is part of a three cartoon set that took first place in the cartoon category of the 2007 A-Mu-sing competition. Free to use in the classroom and on course web sites.

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  • This article presents a dataset containing the 1970 draft lottery information, which illustrates a nonrandom procedure. Key Words: Chi-square; Correlation; Exploratory data analysis; Graphical analysis; Randomness; Regression.
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  • This article presents data for examining the ability of individuals to choose numbers randomly. Three datasets of six-tuples selected by a lottery game, generated by S-Plus, and chosen by college students can be compared using descriptive statistics and goodness of fit tests to explore bias and randomness. Key Words: Boxplots; Chi-squared tests; Minimum gap; QQ plots.
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  • This article describes a dataset on the readability of booklets about cancer and the reading levels of patients with cancer. Students should be familiar with scales of measurement, data reduction, measuring center, constructing and interpreting displays, and reaching conclusions in real problems. Key Words: Ordinal data, Means, Medians, Histograms
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