Note that, the first in a row on the regression analysis performs a simple linear model (an X-variable), with the least squares method for the estimation of the coefficients in the model. Adapted the standard error of the estimate, R-squared and standard errors of the coefficients are all presented and explained. The representation of formula is reduced to a minimum, and an illustrative example is the note. . This note, the first in a series on regression analysis Introd … Read more »

Note that, the first in a row on the regression analysis performs a simple linear model (an X-variable), with the least squares method for the estimation of the coefficients in the model. Adapted the standard error of the estimate, R-squared and standard errors of the coefficients are all presented and explained. The representation of formula is reduced to a minimum, and an illustrative example is the note. . Note that, the first in a row on the regression analysis performs a simple linear model (an X-variable), with the least squares method for the estimation of the coefficients in the model. Adapted the standard error of the estimate, R-squared and standard errors of the coefficients are all presented and explained. The representation of formula is reduced to a minimum, and an illustrative example is the note.
This is a Darden case study.
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Phillip E. Pfeifer
Source: Darden School of Business
11 pages.
Publication Date: Aug 20, 1996. Prod #: UV0131-PDF-ENG
Introduction to Least Squares Modeling HBR case solution