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  • Dataset: The "Unusual Episode" Data Revisited

    This article describes a dataset containing information on economic class of passengers and mortality rates from the sinking of the Titanic. The dataset can be used to foster statistical thinking by giving students the data and asking them to determine the source.

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  • Dataset Example: The Statistics of Poverty and Inequality

    This dataset contains a number of variables like birth rate, death rate, life expectancy, and Gross National Product for 97 countries. Suggested activities are geared toward non-mathematicians and include exploratory graphical analyses to answer several central questions. Key words: boxplot, scatterplot, population growth

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  • Dataset Example: What's Normal? -- Temperature, Gender, and Heart Rate

    This article describes a dataset on body temperature, gender, and heart rate. It addresses concepts like true means, confidence intervals, t-statistics, t-tests, the normal distribution, and regression.

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  • Dataset Example: NFL Y2K PCA

    This article describes a dataset on the 2000 National Football League (NFL) regular season and the exploratory data analyses performed. Key Words: Multivariate analysis; Summary ranking measures

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  • Dataset Example: Investigating Home Court Advantage

    This article presents data from 1997 Big Ten Conference men's basketball games involving the University of Iowa Hawkeyes. The data can be used to demonstrate bivariate statistical inference techniques such as confidence regions, paired comparisons, and simultaneous confidence intervals. Key Word: Bivariate data; Scatterplot.

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  • Teaching Statistics with Data of Historic Significance: Galileo's Gravity and Motion Experiments

    This article describes Galileo's data on falling bodies and projectiles and its use as an aid in teaching polynomial and nonlinear regression. Key Words: Independent and dependent variables; Graphical analysis.

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  • Exploring Relationships in Body Dimensions

    This article presents a dataset containing physical measurements for 507 physically active individuals. These data can be used to demonstrate simple descriptive statistics, least squares and multiple regression, or discriminant and classification analysis. The data are in .dat format.

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  • DIG Stats: Cloud Seeding Activity

    In this activity, students will perform a two-way ANOVA on a dataset containing rainfall amounts for seeded and unseeded clouds in each of the 4 seasons. Questions about the exercise are given as well as a link to Excel instructions. The data exist in Excel and text formats.

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  • DIG Stats: Health Insurance Activity

    In this activity, students will perform a chi-squared test on the number of people with health insurance by age to determine whether there is a relationship between age and insurance coverage. Questions about the exercise and a link to the DIG Stats Online Chi-Squared Calculator are given. The data exist in Excel and text formats.

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  • DIG Stats: Football Activity

    In this activity, students will perform a t-test to determine if there is a significant difference between the kicking distances of a football filled with helium and one filled with regular air. Questions about the exercise and links to Excel and TI-83 instructions are given. The data exist in Excel, TI-83, and text formats.

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