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  • Against All Odds: 28. Inference for Proportions

    This free online video program "marks a transition in the series: from a focus on inference about the mean of a population to exploring inferences about a different kind of parameter, the proportion or percent of a population that has a certain characteristic. Students will observe the use of confidence intervals and tests for comparing proportions applied in government estimates of unemployment rates."

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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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  • 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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  • Incorporating Data Analysis Projects into Introductory Statistics

    This 21 page pdf file includes teaching tips for using projects when teaching statistics such as group formation and grading rubrics. This site provides sample projects on data and probability summaries, hypothesis testing and simple linear regression.

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  • Project #2: Probability Summary

    This assignment has students investigate whether the risk of having a child with a low birth weight is higher when the mother drinks and smokes during pregnancy. The data set represents a random sample of 1450 births from the state of North Carolina.

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  • Sampling SIM Program: P-values and Standard Distributions

    This webpage provides instructions for teaching p-values and standard distributions using Sampling SIM software. It includes information regarding prerequisite knowledge, common misconceptions, and objectives, as well as links to an activity and a pre/post-test.

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  • Interpreting Statistical p-values

    This page discusses the understanding of and interpretation of p-values for those who read articles with statistical information.

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  • P Values and Statistical Significance

    This resource defines what a p-value is, why .05 is significant, and when to use it. It also covers related topics such as one-tailed/two-tailed tests and hypothesis testing.

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