PSYC 2040 Chapter Notes - Chapter 10: Partial Correlation, Standard Deviation, And1
10 Jan 2016
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Multiple regression and multiple correlation are concerned with the relationship of one variable to a number of other variables. Multiple regression and multiple correlation are two aspects of the same analytic procedure. Multiple regression measures the nature of the correlation between one dependent/criterion variable (y) with a collection of independent/predictor variables (xs). [see text, p. 214 equation 1 (multiple regression equation in raw data form)]. a = the constant (i. e. the value of y" when all of the x values are 0) X = the predictors in raw score forms. When the variables are expressed in z scores, the equation is modified into the following. [see text p. 214, equation 2 (multiple regression equation in z score form)]. Z"y = the predicted value of zy. 1, 2 are the standardized regression coefficients. Z1, z2 are the predictors in z score form.
