Question

Correlation and Regression True or False 3 Questions:

K). In simple linear regression predicting Y from X, the unstandardized coefficient of the X variable will always equal the Pearson r between X and Y. (Assume X and Y are not measured as z scores).

L). In simple linear regression predicting Y from X, the standardized coefficient of the X variable will always equal the Pearson r between X and Y.

M). In multiple regression predicting Y from X, the standardized coefficient for the first X variable will always equal the Pearson r between that X and Y.

Assume that all of the assumptions for correlation and linear regressions have been met (including the assumption that the X and Y variables are each normally distributed).

Answer 1

Pearson's r between X and Y is the standardized slope coefficient of a simple linear regression line. Thus,

K). In simple linear regression predicting Y from X, the unstandardized coefficient of the X variable will always equal the Pearson r between X and Y. - False

L). In simple linear regression predicting Y from X, the standardized coefficient of the X variable will always equal the Pearson r between X and Y. - True

M). In multiple regression predicting Y from X, the standardized coefficient for the first X variable will always equal the Pearson r between that X and Y. - False

The correct statement is,

In multiple regression predicting Y from X, the standardized coefficient for the first X variable will always equal the partial Pearson r between that X and Y.