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QUESTION 5 Continue to use the regression results in column (1) from the table in Question 4. Construct a 95% confidence interval for the coefficient on "Graduated high school". Lower bound: Upper bound: Please report all answers in this question to four decimal places.

QUESTION 5 Continue to use the regression results in column (1) from the table in Question 4. Construct a 95% confidence interval for the coefficient on "Graduated high school". Lower bound: Upper bound: Please report all answers in this question to four decimal places.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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please answer question 5 only. i already have answer for question 4, thanks.

 

(Just in case if you need question 4 answer )

answer (4)

Test Statistic F is 21.87 

We conclude that The p-value is < .00001. The result is significant at p < .05.

Fail to reject null hypothesis. 

Answer is "no". 

 

QUESTION 5 Continue to use the regression results in column (1) from the table in Question 4. Construct a 95% confidence interval for the coefficient on "Graduated high school". Lower bound: Upper bound: Please report all answers in this question to four decimal places.
Transcribed Image Text:QUESTION 5 Continue to use the regression results in column (1) from the table in Question 4. Construct a 95% confidence interval for the coefficient on "Graduated high school". Lower bound: Upper bound: Please report all answers in this question to four decimal places.
QUESTION 4 The table below is used for Questions 4 and 5. It contains three estimated regressions, which were computed in 2007 using data on employees. The data set used for the regressions consisted of information on over 10,000 full-time, full-year workers. Employees were surveyed on their earnings and whether they had graduated high school or not. The data set also contains information on the region of the country where the person lived (North / East / South / West), and the individual's gender and age. For the purposes of this quiz: AHE = average hourly earnings Graduated high school (X1) = binary variable (1 if the employee graduated high school, 0 if they did not) Male (X2) = binary variable (1 if male, O if female) Age (X3) = age in years North (X4) = binary variable (1 if Region = North, 0 otherwise) South (X5) = binary variable (1 if Region = South, 0 otherwise) East (X6) = binary variable (1 if Region = East, 0 otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using 2007 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor Graduated high school (X¡) 0.352 0.373 0.371 (0.021) (0.021) (0.021) Male (X2) 0.458 0.457 0.451 (0.021) (0.020) (0.020) Age (X3) 0.011 0.011 (0.001) (0.001) North (X4) 0.175 (0.37) South (Xs) 0.103 (0.033) East (X6) -0.102 (0.043) Intercept 12.84 12.471 12.390 (0.018) (0.049) (0.057) F-statistic for regional effects = 0 21.87 SER 1.026 1.023 1.020 R? 0.0710 0.0761 0.0814 n 10973 10973 10973 Using the regression results in column (1): Is the coefficient on "Graduated high school", estimated from this regression, statistically significant at the level? The calculated test statistic is (two decimal places) Therefore, is the null hypothesis rejected at the 5% level of significance? (Type Yes or No)
Transcribed Image Text:QUESTION 4 The table below is used for Questions 4 and 5. It contains three estimated regressions, which were computed in 2007 using data on employees. The data set used for the regressions consisted of information on over 10,000 full-time, full-year workers. Employees were surveyed on their earnings and whether they had graduated high school or not. The data set also contains information on the region of the country where the person lived (North / East / South / West), and the individual's gender and age. For the purposes of this quiz: AHE = average hourly earnings Graduated high school (X1) = binary variable (1 if the employee graduated high school, 0 if they did not) Male (X2) = binary variable (1 if male, O if female) Age (X3) = age in years North (X4) = binary variable (1 if Region = North, 0 otherwise) South (X5) = binary variable (1 if Region = South, 0 otherwise) East (X6) = binary variable (1 if Region = East, 0 otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using 2007 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor Graduated high school (X¡) 0.352 0.373 0.371 (0.021) (0.021) (0.021) Male (X2) 0.458 0.457 0.451 (0.021) (0.020) (0.020) Age (X3) 0.011 0.011 (0.001) (0.001) North (X4) 0.175 (0.37) South (Xs) 0.103 (0.033) East (X6) -0.102 (0.043) Intercept 12.84 12.471 12.390 (0.018) (0.049) (0.057) F-statistic for regional effects = 0 21.87 SER 1.026 1.023 1.020 R? 0.0710 0.0761 0.0814 n 10973 10973 10973 Using the regression results in column (1): Is the coefficient on "Graduated high school", estimated from this regression, statistically significant at the level? The calculated test statistic is (two decimal places) Therefore, is the null hypothesis rejected at the 5% level of significance? (Type Yes or No)
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