Multiple Regression Lab Chapter 10 1 Topics Multiple
Multiple Regression Lab Chapter 10 1
Topics • • Multiple Linear Regression Effects Levels of Measurement Dummy Variables 2
Multiple Linear Regression 3
Output from Regressing INCOME 86 on EDUC, AGE, and SEX
Model Summary • Multiple correlation coefficient R – Correlation of all IV’s with DV – Report strength • Coefficient of determination Adj. R 2 – % of explained variability in DV by all IV’s
ANOVA Table - Size of F and p-value (sig. ) indicate significance of overall model - Large F, small p-value (<. 05 or. 01) is a significant model
Coefficients Table • Similar to bivariate regression – unstandardized coefficients – regression equation
Multiple Linear Regression (cont. ) • standardized coefficients (betas) – net effects – indicate direction and strength 8
Net Effects • Interpretation – “What effect does this variable have separate from the effects of the other independent variables? ” – a way to statistically control for other variables in the model • A potential problem: multicollinearity (more on this in lecture) 9
Levels of Measurement Can it be used in linear regression as Dependent variable Independent variable Interval/ratio variable Ordinal variable Dichotomy Nominal variable (with three or more attributes) yes Yes (but with caution) yes no Maybe (as series of dummy variables) 10
Dummy Variables • a way of getting nominal variables with 3 or more attributes into regression as independent variables • conversion into a series of dichotomies • enter all but one of the dichotomies
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