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Regression

  • This case study assesses the question, "Can the application of magnetic fields be an effective treatment for pain?" It addresses concepts including: boxplots, stem and leaf displays, correlated t-test, two-sample t-test, repeated measures analysis of variance, and analysis of covariance.
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  • This case study addresses the question: "Will a smiling person accused of a crime be treated more leniently than one who is not smiling? If so, does the type of smile make a difference?" It concerns the following concepts: quantile/boxplots, contrasts among means, Dunnett's test, and Bonferroni correction.
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  • This case study covers the concepts including: boxplots, stem and leaf displays, two-sample t tests, and analysis of variance. It also assesses the question, "Does an instructor's reputation affect ratings of the instructor's lecture?"
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  • This case study compares a low-fat diet to a "Mediterranean diet" to see which led to better health. Concept: Chi Square test of independence
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  • This case study aims to answer the question, "How does one select employees to perform physically demanding jobs?" It examines the relationship between isometric strength tests and job performance for 147 workers. Concepts: correlation, linear regression, multiple regression.
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  • This case study covers the following concepts: confidence intervals for proportions and the normal approximation to the binomial. It also assesses the question: "What proportion of the iMac purchasers are new computer owners?"
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  • This case study assesses the question, "Is it easier to learn to use computer software that uses natural language commands?" Concepts: analysis of covariance, adjusted means, boxplots
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  • This case study assesses the question, "Do physicians discriminate against overweight patients?" This study indicates that, at least in one respect, they do. Concepts: t-test, means, boxplots
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  • In this free online video program, "students will understand inference for simple linear regression, emphasizing slope, and prediction. This unit presents the two most important kinds of inference: inference about the slope of the population line and prediction of the response for a given x. Although the formulas are more complicated, the ideas are similar to t procedures for the mean sigma of a population."

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  • This tutorial on Multiple Regression helps students understand the definition, use the standard error of estimate, use rank correlation, and solve exercise problems using multiple regression.
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