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(1) The table below shows the results of a linear regression using data from the 2021 General Social Survey (GSS). These are survey data so

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(1) The table below shows the results of a linear regression using data from the 2021 General Social Survey (GSS). These are survey data so the unit of observation is an individual survey respondent. The regression model predicts responses to the question "How do you feel when you think about differences in wealth between the rich and the poor in America?" where 0 indicates "not angry at all" and 10 indicates "extremely angry". The predictors are age (in years), education (in years) and a dummy variable for female. The number of observations is 1,676. Variable Coefficient Std. Error (Intercept) 4.22 .39 Age -.02 01 Education 14 04 Female .47 09 (a) What is the predicted value of the dependent variable for a 20-year-old female with 15 years of education? (b) What is the predicted value of the dependent variable for a 50-year-old male with 13 years of education? (c) Graph predicted relationship between education and the dependent variable for a 30-year-old man. (d) On the same plot from (c), draw a dashed line plotting the predicted relationship between ed- ucation and the dependent variable for a 75-year-old woman. (e) What can you say overall about the relationship between education and feelings about inequal- ity (when controlling for age and gender as in the regression table) based on these regression results? Specifically be sure to comment on both statistical significance, defining both the the null and alternative hypotheses and saying whether you'd reject or fail to reject the null, as well as what that result tells you. Also comment on the size of the coefficient estimate, interpreting it relative to the scales of both education and the dependent variable, explaining whether you think this is a big relationship or not

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