linear regression doubt.

Question 1 1 pts Suppose the following are the results of a linear regression with the unemployment rate in decimal form as the dependent variable and population density and local tax rate as the independent variables. The local tax rate is a percentage in decimal form. The coefficient on population density is -0.00002 with a p-value of 0.0001. The coefficient on the number of local tax rate is 0.258 with a p-value of 0.8576. What can be said about the relationship between the unemployment rate and the local tax rate? Increasing the local tax rate by 0.05 increases the unemployment rate by 0.0129 Increasing the local tax rate by 0.05 increases the unemployment rate by 0.258 Increasing the local tax rate by 0.05 increases the unemployment rate by 0.8576 O At a 5% Level of Significance, the local tax rate has a statistically significant impact on the unemployment rate Question 2 1 pts Suppose you estimate a Linear Regression with housing prices as the dependent variable and education and income as independent variables. From this Linear Regression, you get an Adjusted R-squared of 0.1545. When you add air pollution as an independent variable to the Linear Regression, the Adjusted R-squared is 0.1938. What does this indicate? O The Goodness-of-Fit as measured by Adjusted R-squared has gotten better Air pollution doesn't contribute very much to the Goodness-of-Fit of the Linear Regression Since R-squared and Adjusted R-squared are different, these results indicate that Goodness-of-Fit has gotten worse after adding air pollution as an independent variable Adjusted R-square doesn't contain information about the Goodness-of-Fit of a Linear RegressionQuestion 3 1 pts Consider the Categorical Variable Self-Reported Health Status with the following categories: Good, Fair, Poor. The dependent variable in the Linear Regression is Health Insurance Premium in dollars. Suppose Fair is the excluded category. The coefficient on Good is -1,403. The coefficient on Poor is 2,906. What is the interpretation of the coefficient on Poor? O People who report Good health pay $1,403 less in Health Insurance Premiums compared to a person who reports Poor health A person who reports Poor health pays $2,906 more in Health Insurance Premiums compared to a person who reports Good health O A person who reports Poor health pays $2,906 more in Health Insurance Premiums compared to a person who reports Fair health O There is no way to determine from these results how the Health Insurance Premiums of people who report Poor health compare to the premiums of people who report other health statuses Question 4 1 pts Suppose the coefficient on Age is -4.376 and the coefficient on Age_squared is 0.0714. What does the Quadratic Relationship look like? It's a straight upward sloping relationship It's a straight downward sloping relationship It's a Hill-Shaped relationship It's a U-Shaped relationshipConsider the Binary Dummy Variable Gender which takes the values "M" and "F". In a Linear Regression with the dependent variable Income in dollars, Gender is interacted with Years of Work Experience. Suppose the excluded category for Gender is "F". If the coefficient on Gender is 13,470, the coefficient on Years of Work Experience is 5,483, and the coefficient on the Interaction Term, Years of Work Experience* Gender is 1,026, what is the relationship between Years of Work Experience and Income for a person whose Gender is category "M"? One more Year of Work Experience increases Income by $18,953 One more Year of Work Experience increases Income by $13,470 One more Year of Work Experience increases Income by $6,509 One more Year of Work Experience increases Income by $5,483 Question 6 1 pts Suppose the following are the results of a linear regression with the unemployment rate in decimal form as the dependent variable and population density and local tax rate as the independent variables. The local tax rate is a percentage in decimal form. The coefficient on population density is -0.00002 with a p-value of 0.0001. The coefficient on the number of local tax rate is 0.258 with a p-value of 0.8576. What can be said about the relationship between the unemployment rate and population density? Increasing population density by 1,000 increases the unemployment rate by 0.1 Increasing population density by 1,000 decreases the unemployment rate by 0.00002 Increasing population density by 1,000 decreases the unemployment rate by 0.02 O At a 5% Level of Significance, population density doesn't have a statistically significant impact on the unemployment rateQuestion 7 1 pts Consider the Binary Dummy Variable Student in a Linear Regression where the dependent variable is Monthly Expenditures. The Binary Dummy Variable Student takes a value of "Y" if the person is currently a student and takes a value of "N" if the person isn't currently a student. Suppose the excluded category is "N". The coefficient on the category "Y" is 48.96. Income in dollars is another independent variable with the coefficient 0.549. What is the interpretation of the coefficient on the category "Y"? The average student spends $48.96 in a month The average non-student spends $48.96 in a month For a student, another $1 of income results in that person spending $49.51 more a month O The average student spends $48.96 more a month compared to the average non-student Question 8 1 pts Suppose you conduct the Davidson-Mackinnon Test to compare a Log-Linear Model with a Log-Log Model. You add the predicted values from the Log-Log Model as an additional independent variable in the Log-Linear Model and re-estimate the Log-Linear Model. The coefficient in the re-estimated Log- Linear Model on the predicted values from the Log-Log Model has a p-value of 0.002. At a Level of Significance of 5%, what does the result of the Davidson-Mackinnon Test suggest in this case? The Log-Linear Model is the preferred specification The Log-Log Model is the preferred specification O Quadratic and other higher-power terms of the independent variables should be added to the regression Quadratic and other higher-power terms of the independent variables should be excluded from the regressionQuestion 9 1 pts Suppose the coefficient on Age is 5.748 and the coefficient on Age_squared is -0.045. What is the formula for the Marginal Effect of Age? O 5.748*Age - 0.045*Age_squared O 5.748 - 2*0.045*Age O 5.748*Age O 5.748 - 0.045 Question 10 1 pts Consider the Categorical Variable Self-Reported Health Status with the following categories: Good, Fair, Poor. The dependent variable in the Linear Regression is Health Insurance Premium in dollars. Suppose Fair is the excluded category. The coefficient on Good is -1,403. The coefficient on Poor is 2,906. What is the interpretation of the coefficient on Good? O People who report Good health pay $1,403 less in Health Insurance Premiums compared to a person who reports Poor health People who report Good health pay $1,403 less in Health Insurance Premiums compared to a person who reports Fair health O People who report Fair health pay $1,403 less in Health Insurance Premiums compared to a person who reports Good health O There is no way to determine from these results how the Health Insurance Premiums of people who report Good health compare to the premiums of people who report Fair health