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  • Smiles and Leniency

    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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  • Magnets and Pain Relief

    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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  • Weapons and Aggression

    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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  • Robustness of t test and ANOVA

    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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  • Unequal n ANOVA and Types of Sums of Squares

    This simulation illustrates types of sums of squares in a 2 x 3 ANOVA.

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  • Regression to the Mean

    This is a simulation illustrating the regression toward the mean phenomenon.

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  • Histograms, Bin Widths, and Cross Validation

    This applet demonstrates how a histogram is affected by bin width and starting point of first bin. It also illustrates cross-validation criterion for assessing histograms.

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  • Dataset Example: Reliability and Regression Analysis

    This applet demonstrates how the reliability of X and Y affect various aspects of the regression of Y on X.

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  • 2 x 2 Contingency Tables

    This applet simulates experiments using 2 x 2 contingency tables. You specify the population proportions and the sample size and examine the effects on the probability of rejecting the null hypothesis.

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  • Chi Square Test of Deviations from Expected Frequencies

    The applet allows users to sample from a normal distribution or from a uniform distribution. It shows the expected values and the observed values and computes the deviation. Then, a chi-square test shows if the deviations are significant for both the normal and uniform distributions.

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