Variables Entered/Removeda Variables Variables Entered Removed Model 1 Method Highest Year of School . Enter Completedb a. Dependent Variable: Age of Respondent b. All requested variables entered. Model Summary Model R .254a 1 R Square Adjusted R Std. Error of the Square Estimate .064 .064 17.232 a. Predictors: (Constant), Highest Year of School Completed ANOVAa Model 1 Sum of Squares Regression df Mean Square 30809.743 1 30809.743 Residual 447218.137 1506 296.958 Total 478027.880 1507 F Sig. 103.751 .000b a. Dependent Variable: Age of Respondent b. Predictors: (Constant), Highest Year of School Completed Coefficientsa Standardized Unstandardized Coefficients Model 1 B (Constant) Highest Year of School Completed a. Dependent Variable: Age of Respondent Std. Error 65.114 1.966 -1.515 .149 Coefficients Beta t -.254 Sig. 33.112 .000 -10.186 .000 Instructions Load the data file called unit 10_SPSSHW7_data_regression.sav. This is a data file based on a 1991 U.S. General Social Survey. First, familiarize yourself with the variables; the data file contains more than 40 variables for each of about 1500 respondents. The variable \"prestg80\" is a scale (i.e., continuous) variable that codes a respondent's occupational prestige (a higher value indicates a more prestigious occupation). You will investigate which other variables predict the occupational prestige score by conducting the following: 1. Conduct a multiple regression to determine whether and to what extent occupational prestige is predicted by the following variables: respondent's sex, cultural sensitivity (sensitivity), number of children they have (childs), the highest year of school completed (educ), and whether the respondent takes illegal drugs (hth5) or has a drinking problem (hlth4). Make sure to check diagnostics and remedy any problems before moving on to #2 below (4 points) 2. Report the results of the analysis (Hint: please refer to the textbook for information about the appropriate way of presenting results). Make sure to report the following: a. method of entry of variables. b. significance of all effects. c. standardized beta coefficients of all effects. d. standardized confidence intervals of all effects. 3. Interpret the results, focusing on the relative strength and reliability of effects