SOC/CJ Use the States data set to analyze the rate of car theft (Carthft12). The independent variables will be population density (Popdense) and unemployment rate (Unemployment)

● Click Analyze S Regression S Linear.

● Move Carthft12 to the “Dependent” window and Popdense and Unemployment to the “Independent”

window.

● Click Statistics and check “Descriptives.” Click Continue to return to the “Linear Regression”

screen.

● Click OK.

a. State the unstandardized multiple regression equation. (HINT: The values for a and b are in the “Coefficients” box of the output, under the column labeled B. The value in the first row is a and the values in the second and third rows are the slopes or b.)

Y 5 ___ 1 ___ X1 1 ___ X2

b. State the standardized multiple regression equation. What is the direction of each relationship?

Which independent variable had the stronger effect on Carthft12? (HINT: The beta-weights are in the “Coefficients” box, under “Standardized Coefficients” and “Beta.”)

Zy 5 ____ Z1 1 ___ Z2

c. Report the value of R2

. What percentage of the variance in Carthft12 is explained by the two independent variables combined? How does this compare to the amount of the variance explained by each independent variable alone? (HINTS: R2 is in the “Model Summary” box and you can compute r

2 from the r’s in the “Correlations” window of the output.)

Bivariate: r r 2 Carthft12 and Popdense Unemployment Multiple: R 2 5