Data Management & Organization

  • This article describes a dataset containing information for 25 brands of domestic cigarettes. The dataset can be used to illustrate multiple regression, outliers, and collinearity.
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  • 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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  • This article describes a dataset containing Major League Baseball data from seasons 1969 through 2000 and illustrates how this data can be used as a course long project covering basic data management, the use of exploratory data analysis to "clean" data, and construction of regression models. The data is in .dat format.
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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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  • JOpenChart is a free Java Toolkit and library for embedding charts into different kinds of applications, no matter if they are server side, desktop or web applications.

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  • This online textbook provides information on the statistical analysis of nutritional data. Techniques covered include data cleaning, descriptive statistics, histograms, graphics, scatterplots, outlier identification, regression and correlation, confounding, and interactions. Each chapter includes exercises with real data and self-tests to be used with SPSS.
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  • This free online video program uses historical anecdotes and contemporary applications to introduce the series which "explores the vital links between statistics and our everyday world. The program also covers the evolution of the discipline."
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  • With this free online video program, "students will see how key characteristics in the distribution of a histogram - shape, center, and spread - help professionals make decisions in such diverse fields as meteorology, television programming, health care, and air traffic control. Through a discussion of the advantages of back-to-back stem plots, this program also emphasizes the importance of seeking explanations for gaps and outliers in small data sets." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 2. Picturing Distributions" and click the "VOD" icon at the top-right of the description.
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  • This chapter of the NIST Engineering Statistics handbook describes Exploratory Data Analysis with an introduction, a discussion of the assumptions, a description of the techniques used, and a set of case studies.
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  • This part of the NIST Engineering Statistics handbook contains case studies for the process improvement chapter, which deals with design of experiments.
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