1. Using the GSS, analyze the relationship between respondents' highest year of school completed (EDUC) and their occupational prestige (PRESTG80). First, run a scattergram of this relationship (Graphs-Legacy Dialogs-Scatter/Dot). Then, estimate the regression equation (Analyze-Regression-Linear). Based on your output, answer the following questions: a. Does the relationship between these variables appear linear? b. Is the relationship positive or negative? c. Are there any outliers apparent in the scatterplot? d. What is the regression equation describing the effect of education (EDUC) on occupational prestige (PRESTG80)? e. Give an interpretation of a and b in that equation. f. How much of the variance in occupational prestige is explained by education? How much is unexplained? g. Is the relationship between education and occupational prestige statistically significant? 2. Repeat steps d through g above to analyze the relationship between highest year of school completed (EDUC) and number of children born (CHILDS). 3. Compute and interpret the correlation (analyze-correlate-bivariate) between the frequency of sex during the past year (SEXFREQ) and the following variables: highest year of school completed (EDUC), total family income (INCOME98), size of place (SIZE), and church attendance (ATTEND). Which of these variables is most strongly correlated with sex frequency? Which correlations are positive and which are negative? Using 2-tailed tests, which correlations are statistically significant? 1. Using the GSS, analyze the relationship between respondents' highest year of school completed (EDUC) and their occupational prestige (PRESTG80). First, run a scattergram of this relationship (Graphs-Legacy Dialogs-Scatter/Dot). Then, estimate the regression equation (Analyze-Regression-Linear). Based on your output, answer the following questions: a. Does the relationship between these variables appear linear? b. Is the relationship positive or negative? c. Are there any outliers apparent in the scatterplot? d. What is the regression equation describing the effect of education (EDUC) on occupational prestige (PRESTG80)? e. Give an interpretation of a and b in that equation. f. How much of the variance in occupational prestige is explained by education? How much is unexplained? g. Is the relationship between education and occupational prestige statistically significant? 2. Repeat steps d through g above to analyze the relationship between highest year of school completed (EDUC) and number of children born (CHILDS). 3. Compute and interpret the correlation (analyze-correlate-bivariate) between the frequency of sex during the past year (SEXFREQ) and the following variables: highest year of school completed (EDUC), total family income (INCOME98), size of place (SIZE), and church attendance (ATTEND). Which of these variables is most strongly correlated with sex frequency? Which correlations are positive and which are negative? Using 2-tailed tests, which correlations are statistically significant