The Racing Car Problem |
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Authors: | Aaron Tenenbein |
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Affiliation: | New York University , USA |
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Abstract: | An approach to teaching linear regression with unbalanced data is outlined that emphasizes its role as a method of adjustment for associated regressors. The method is introduced via direct standardization, a simple form of regression for categorical regressors. Properties of regression in the presence of association and interaction are emphasized. Least squares is introduced as a more efficient way of calculating adjusted effects for which exact decompositions of the variance are possible. Interval-scaled regressors are initially grouped and treated as categorical; polynomial regression and analysis of covariance can be introduced later as alternative methods. |
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Keywords: | Teaching methods Linear regression Unbalanced data Direct standardization Analysis of variance |
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