Regression

  • This archive contains datasets from articles in the Journal of the American Statistical Association.
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  • MacAnova is a free, noncommercial, interactive statistical analysis program for Windows 95/98/NT, Windows 3.1 with Win32s, Macintosh and Unix. MacAnova has many capabilities but its strengths are analysis of variance and related models, matrix algebra, time series analysis (time and frequency domain), and (to a lesser extent) uni-variate and multi-variate exploratory statistics.
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  • Lisp-Stat is an extensible statistical computing environment for data analysis, statistical instruction and research, with an emphasis on providing a framework for exploring the use of dynamic graphical methods. The object-oriented programming system is also used as the basis for statistical model representations, such as linear and nonlinear regression models and generalized linear models. Many aspects of the system design were motivated by the S language.
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  • ViSta constructs very-high-interaction, dynamic graphics that show you multiple views of your data simultaneously. The graphics are designed to augment your visual intuition so that you can better understand your data.

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  • This collection is organized as discussions and activities in the subjects of descriptive statistics, inferential statistics, graphical analysis, and TI-83 and Excel guides. It also includes a section of quizzes. Key Words: Mean; Median; Mode; Normal Distribution; Skewed Distribution; Range; Standard Deviation; Confidence Interval; T-Test; ANOVA; Correlation; Regression; Chi-Square; Probability Distributions; Histograms; Scatterplots; Boxplot.
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  • 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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  • This case study aims to answer the question, "How does one select employees to perform physically demanding jobs?" It examines the relationship between isometric strength tests and job performance for 147 workers. Concepts: correlation, linear regression, multiple regression.
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  • In this free online video program, "students will understand inference for simple linear regression, emphasizing slope, and prediction. This unit presents the two most important kinds of inference: inference about the slope of the population line and prediction of the response for a given x. Although the formulas are more complicated, the ideas are similar to t procedures for the mean sigma of a population."

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  • This self-test provides a review/assessment of the Probability section of this module. At the bottom, there is a grading button to rate the users' understanding of the material.
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  • This tutorial includes using, finding, weighting, and solving problems with Moving Averages.
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