Run a regression of Earnings on Height. Is the estimated slope statistically significant? A. Yes. B. No. Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors i The 95% confidence interval for the slope coefficient is [ (Round your responses to three decimal places) ☐] Run a regression of Earnings on Height using data for female workers only. Is the estimated slope statistically significant? A. Yes. B. No. Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors The 95% confidence interval for the slope coefficient is [ (Round your responses to three decimal places) ☐ Run a regression of Earnings on Height using data for male workers only. Is the estimated slope statistically significant? A. Yes. B. No. Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors The 95% confidence interval for the slope coefficient is (☐, ☐ ] (Round your responses to three decimal places) Run a regression of Earnings on Height using data for female workers only. Is the estimated slope statistically significant? A. Yes. B. No. Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors i The 95% confidence interval for the slope coefficient is [ Run a regression of Earnings on Height using data for male workers only. Is the estimated slope statistically significant? (Round your responses to three decimal places) A. Yes. O B. No. Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors The 95% confidence interval for the slope coefficient is [ (Round your responses to three decimal places) Can you reject the null hypothesis that the effect of height on earnings is the same for men and women? A. Yes. B. No.

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4A: Problems In Applying The Linear Regression Model

Section: Chapter Questions

Problem 2E

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Question

In this exercise, you will investigate the relationship between earnings and height.

These data are taken from the US National Health Interview Survey for 1994. Download the data from the table by clicking the download table icon

A detailed description of the variables used in the dataset is available here

Use a statistical package of your choice to answer the following questions.

Earnings and Height,,
Earnings,Height,Sex
84141.75,59,0
84062.75,59,0
7715.8540039063,59,0
84130.75,59,0
84131.75,60,0
44119.16015625,60,0
17229.263671875,60,0
84067.75,60,0
84123.75,60,0
84014.75,60,0
38979.3359375,60,0
33717.96875,60,0
44097.16015625,61,0
33753.96875,61,0
49443.109375,61,0
84062.75,61,0
33755.96875,61,0
28552.38671875,61,0
44214.16015625,61,0
83991.75,61,0
44095.16015625,61,0
33787.96875,61,0
83978.75,61,0
84071.75,61,0
28470.38671875,61,0
33698.96875,61,0
49482.109375,61,0
33732.96875,62,0
18255.841796875,62,0
44140.16015625,62,0
84133.75,62,0
84060.75,62,0
44114.16015625,62,0
83995.75,62,0
10793.4287109375,62,0
84077.75,62,0
23397.873046875,62,0
38998.3359375,62,0
84026.75,62,0
84020.75,62,0
84017.75,62,0
23399.873046875,62,0
44140.16015625,62,0
84090.75,62,0
44055.16015625,62,0
84095.75,62,0
84066.75,62,0
23381.873046875,62,0
23299.873046875,63,0
49365.109375,63,0
9825.505859375,67,1
83959.75,67,1
23349.873046875,67,1
38863.3359375,67,1
20239.509765625,67,1
33794.96875,67,1
84022.75,67,1
84049.75,67,1
5724.8955078125,67,1
44198.16015625,68,1
84041.75,68,1
83982.75,68,1
33683.96875,68,1
38950.3359375,68,1
84113.75,68,1
84000.75,68,1
84152.75,68,1
84096.75,68,1
44219.16015625,68,1
44161.16015625,68,1
84013.75,68,1
84071.75,68,1
49443.109375,68,1
84135.75,68,1
84027.75,68,1
84014.75,68,1
10838.4287109375,68,1
83961.75,68,1
33800.96875,68,1
83986.75,68,1
44117.16015625,68,1
84078.75,68,1
84080.75,68,1
83966.75,68,1
84019.75,68,1
44199.16015625,68,1
28528.38671875,68,1
84110.75,68,1
84141.75,68,1
17071.263671875,68,1
23289.873046875,68,1
84073.75,68,1
84075.75,68,1
83970.75,69,1
84129.75,69,1
38957.3359375,69,1
28581.38671875,69,1
33676.96875,69,1
84011.75,69,1
23380.873046875,69,1
,,

Run a regression of Earnings on Height.
Is the estimated slope statistically significant?
A. Yes.
B. No.
Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors i
The 95% confidence interval for the slope coefficient is [
(Round your responses to three decimal places)
☐]
Run a regression of Earnings on Height using data for female workers only.
Is the estimated slope statistically significant?
A. Yes.
B. No.
Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors
The 95% confidence interval for the slope coefficient is [
(Round your responses to three decimal places)
☐
Run a regression of Earnings on Height using data for male workers only.
Is the estimated slope statistically significant?
A. Yes.
B. No.
Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors

The 95% confidence interval for the slope coefficient is (☐, ☐ ]
(Round your responses to three decimal places)
Run a regression of Earnings on Height using data for female workers only.
Is the estimated slope statistically significant?
A. Yes.
B. No.
Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors i
The 95% confidence interval for the slope coefficient is [
Run a regression of Earnings on Height using data for male workers only.
Is the estimated slope statistically significant?
(Round your responses to three decimal places)
A. Yes.
O B. No.
Construct a 95% confidence interval for the slope coefficient using heteroskedasticity-robust standard errors
The 95% confidence interval for the slope coefficient is [
(Round your responses to three decimal places)
Can you reject the null hypothesis that the effect of height on earnings is the same for men and women?
A. Yes.
B. No.

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