Laboratories

  • This resource defines and explains the median using an example on employee salaries.
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  • This resource defines and explains percent changes using an example on city murder rates.
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  • This resource defines and explains per capita rates using an example on city murder rates.
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  • This resource explains margin of error using an example on presidential popularity polls.
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  • This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

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  • This resource discusses sample sizes and how they are chosen.
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  • This resource explains the t-distribution and hypothesis testing (informally) using an example on laptop quality.
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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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  • This applet allows students to explore three methods for measuring "goodness of fit" of a linear model. Users can manipulate both the data and the regression line to see changes in the square error, the absolute error, and the shortest distance from the data point to the regression line.
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  • This lesson poses a series of questions designed to challenge students' possible misconceptions of statistical inference and hypothesis testing. The lesson uses the statistical software, Fathom, and three datasets with information on the number of chips per canister distributed by a snack maker. The data can found at the relation address below.
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