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  • This activity focuses on basic ideas of linear regression. It covers creating scatterplots from data, describing the association between two variables, and correlation as a measure of linear association. After this activity students will have the knowledge to create output that yields R-square, the slope and intercept, as well as their interpretations. This activity also covers some of the basics about residual analysis and the fit of the linear regression model in certain settings. The corresponding data set for this activity, 'BAC data', can be found at the following web address: http://www.causeweb.org/repository/ACT/BAC.txt

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  • This activity explains the important features of a distribution: shape, center, spread, and unusual features. It also covers how to determine the difference between mean and median, and their respective measures of spread, as well as when to apply them to a particular distribution. Graphical displays such as: histograms and boxplots are also introduced in this activity. The corresponding data set for this activity is found at the following web address: http://www.causeweb.org/repository/ACT/food.txt

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  • This activity enables students to learn about confidence intervals and hypothesis tests for a population mean. It focuses on the t-distribution, the assumptions for using it, and graphical displays. The activity also focuses on how to interpretations a confidence interval, a p-value, and a hypothesis test.

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  • This collection of case studies includes the following topics: Stock Prices; Breast Cancer Research; Effect of Fitness Program; Water Use in Los Angeles; Oral Hygiene in the ICS-II project; Brinks vs NYC; Effect of Exercise on Heart Disease; National Assessment of Educational Progress; The London Underground; Suicides of Women and Men; Temperature in San Francisco; Lead Intake; Voting for Johnson; Salaries of Yale Men; K-Mart Cookie Sales; Skeleton Differences between Tribes; Advertising for Detergents; Did Mendel Fudge his Data; Rainfall in the United Kingdom; Jury selection in Alameda County; Racial Bias in Jury Selection: Swain vs Alabama.; Gender Bias in Jury Selection: The Case of Dr. Spock.; The ELISA test for the AIDS Virus.; School Careers in the Netherlands in 1959.; The Northridge Earthquake of January 1994.; The Trial of the Pix.

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  • ... we must remember that measures were made for man and not man for measures. a quote of popular science and science fiction author Isaac Asimov (1920 - 1992) in "Of Time and Space and Other Things" page 143, Avon Books, 1965. The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • The words 'model' and 'mode' have, indeed, the same root; today, model building is science a la mode. Quote of american philosopher Abraham Kaplan (1918-1993) appearing in "The Conduct of Inquiry" (Chandler, 1964) p. 258. Also to be found in "Statistically Speaking the dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither p. 140

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  • A cartoon to teach about ambiguous reporting of survey information. 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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  • If you can't measure it, I'm not interested. A quote by Canadian educator and management theorist Laurence Johnston Peter (1919 - 1990) from "Peter's People" in "Human Behavior" (August, 1976; page 9). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • Statistics is the art of stating in precise terms that which one does not know. A quote by American Statistician William Henry Kruskal (1919 - 2005) in his article "Statistics, Moliere, and Henry Adams," in "American Scientist Magazine" (1967; vol. 55, page 417).The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • Normality is a myth; there never has, and never will be, a normal distribution. A quote by Irish statistician and econometrician Roy C. Geary (1896 - 1983) found in "Biometrika" volume 34, 1947, page 241.

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