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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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  • 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 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 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 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 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 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 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: "Does the mere presence of a weapon increase the accessibility of aggressive thoughts?" It concerns the following concepts: quantile and box plots, stem and leaf displays, one-sample t test, confidence interval, within-subjects ANOVA, and consequences of violation of normality assumption.
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  • This applet lets you explore the effect of violations of the assumptions of normality and homogeneity of variance on the type I error rate and power of t tests (and two-group analysis of variance).
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