•   •   •   •

Download the Paper (459 K, PDF file) - January 1, 2004 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
Regression analysis can imply a broader range of techniques that ordinarily appreciated. Statisticians commonly define regression so that the goal is to understand “as far as possible with the available data how the the conditional distribution of some response y varies across subpopulations determined by the possible values of the predictor or predictors” ( Cook and Weisberg, 1999: 27). For example, if there is a single categorical predictor such as male or female, a legitimate regression analysis has been undertaken if one compares two income histograms, one for men and one for women. Or, one might compare summary statistics from the two income distributions: the mean incomes, the median incomes, the two standard deviations of income, and so on. One might also compare the shapes of the two distributions with a Q-Q plot.

SUGGESTED CITATION:
Richard Berk, "Data Mining Within a Regression Framework" (January 1, 2004). Department of Statistics, UCLA. Department of Statistics Papers. Paper 2004010101.
http://repositories.cdlib.org/uclastat/papers/2004010101