Graduate students

  • This article describes a dataset of days in office of US Presidents with outliers that are not mistakes or unusually high or low observations. The data illustrate that outliers need not be errors but could be particularly interesting cases and that data displays may differ in their ability to reveal interesting data structure. Key Words: Inliers; Interpretation in context.
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  • 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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  • This article describes a dataset on life expectancies, densities of people per television set, and densities of people per physician in various countries of the world. The example addresses correlation versus causation and data transformations. Key Word: Prediction.
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  • This article describes a dataset containing energy use data for single-family homes and monthly weather data in the Boston area over a seven year period. The data can help illustrate concepts like central tendency, dispersion, time series analysis, correlation, simple and multiple regression, and variable transformations. Key Words: measurement; forecasting.
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  • The dataset described in this article contains information on 345 plays on an electronic slot machine and the prize for each. This data can be used to illustrate parametric bootstrapping and tests of independence for two and three-way contingency tables involving random zeroes. Key Words: Simulation; Elementary probabilities.
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  • This activity uses Microsoft Excel to estimate the population variance of grouped data two ways: the variance within a group and the variance between groups. This activity accompanies Section 7.3 of Data Matters.
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  • This Compendium describes distributions appropriate for the modeling of random data. The number of distributions (56) is large, including: 1. Continuous distributions (30), (Symmetric (11) and Skewed (19)) 2. Continuous binary mixtures(17), 3. Discrete distributions (5), 4. Discrete binary mixtures (4), All formulas are shown in their fully-parametrized form, not the standard form. Many of the formulas given are seldom described. Random variate generation is included where feasible.
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  • This lesson describes bootstrapping in the context of a statistics class for psychology students.
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  • Users can select from detailed tables and geographical comparison tables to generate data from the 2000 Census.
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  • This is an example of "growing" a decision tree to analyze two possible outcomes. The tree's branches examine the two possible conditions of employee drug use with corresponding probabilities. This example looks at the final outcome probabilities of being correctly and incorrectly identified versus testing accuracy.
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