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 Run a regression of Earnings on Height. Is the estimated slope statistically significant? OA. Yes. OB. 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 0.0 (Round your responses to three decimal places) Run a regression of Earnings on Height using data for female workers only.
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 Run a regression of Earnings on Height. Is the estimated slope statistically significant? OA. Yes. OB. 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 0.0 (Round your responses to three decimal places) Run a regression of Earnings on Height using data for female workers only.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section: Chapter Questions
Problem 22SGR
Related questions
Question
| Earnings and Height | ||
| Earnings | Height | Sex |
| 84004.75 | 59 | 0 |
| 84075.75 | 59 | 0 |
| 7822.854004 | 59 | 0 |
| 84110.75 | 59 | 0 |
| 84098.75 | 60 | 0 |
| 44138.16016 | 60 | 0 |
| 17116.26367 | 60 | 0 |
| 84070.75 | 60 | 0 |
| 84058.75 | 60 | 0 |
| 84089.75 | 60 | 0 |
| 38917.33594 | 60 | 0 |
| 33729.96875 | 60 | 0 |
| 44165.16016 | 61 | 0 |
| 33715.96875 | 61 | 0 |
| 49407.10938 | 61 | 0 |
| 84118.75 | 61 | 0 |
| 33613.96875 | 61 | 0 |
| 28509.38672 | 61 | 0 |
| 44145.16016 | 61 | 0 |
| 84033.75 | 61 | 0 |
| 44218.16016 | 61 | 0 |
| 33661.96875 | 61 | 0 |
| 84025.75 | 61 | 0 |
| 84117.75 | 61 | 0 |
| 28601.38672 | 61 | 0 |
| 33784.96875 | 61 | 0 |
| 49462.10938 | 61 | 0 |
| 33632.96875 | 62 | 0 |
| 18198.8418 | 62 | 0 |
| 44153.16016 | 62 | 0 |
| 83967.75 | 62 | 0 |
| 83994.75 | 62 | 0 |
| 44121.16016 | 62 | 0 |
| 83961.75 | 62 | 0 |
| 10807.42871 | 62 | 0 |
| 83980.75 | 62 | 0 |
| 23410.87305 | 62 | 0 |
| 38952.33594 | 62 | 0 |
| 84014.75 | 62 | 0 |
| 83979.75 | 62 | 0 |
| 84043.75 | 62 | 0 |
| 23369.87305 | 62 | 0 |
| 44170.16016 | 62 | 0 |
| 84056.75 | 62 | 0 |
| 44205.16016 | 62 | 0 |
| 84100.75 | 62 | 0 |
| 84116.75 | 62 | 0 |
| 23388.87305 | 62 | 0 |
| 23400.87305 | 63 | 0 |
| 49370.10938 | 63 | 0 |
| 9938.505859 | 67 | 1 |
| 84063.75 | 67 | 1 |
| 23422.87305 | 67 | 1 |
| 38867.33594 | 67 | 1 |
| 20405.50977 | 67 | 1 |
| 33757.96875 | 67 | 1 |
| 83995.75 | 67 | 1 |
| 84053.75 | 67 | 1 |
| 5689.895508 | 67 | 1 |
| 44102.16016 | 68 | 1 |
| 84127.75 | 68 | 1 |
| 83999.75 | 68 | 1 |
| 33686.96875 | 68 | 1 |
| 38853.33594 | 68 | 1 |
| 83989.75 | 68 | 1 |
| 83992.75 | 68 | 1 |
| 83963.75 | 68 | 1 |
| 84115.75 | 68 | 1 |
| 44229.16016 | 68 | 1 |
| 44102.16016 | 68 | 1 |
| 84088.75 | 68 | 1 |
| 84036.75 | 68 | 1 |
| 49410.10938 | 68 | 1 |
| 84077.75 | 68 | 1 |
| 84118.75 | 68 | 1 |
| 84080.75 | 68 | 1 |
| 10882.42871 | 68 | 1 |
| 84115.75 | 68 | 1 |
| 33665.96875 | 68 | 1 |
| 84142.75 | 68 | 1 |
| 44237.16016 | 68 | 1 |
| 84124.75 | 68 | 1 |
| 84086.75 | 68 | 1 |
| 84007.75 | 68 | 1 |
| 84120.75 | 68 | 1 |
| 44059.16016 | 68 | 1 |
| 28483.38672 | 68 | 1 |
| 84000.75 | 68 | 1 |
| 84044.75 | 68 | 1 |
| 17179.26367 | 68 | 1 |
| 23277.87305 | 68 | 1 |
| 84006.75 | 68 | 1 |
| 84045.75 | 68 | 1 |
| 84016.75 | 69 | 1 |
| 84012.75 | 69 | 1 |
| 38898.33594 | 69 | 1 |
| 28475.38672 | 69 | 1 |
| 33658.96875 | 69 | 1 |
| 84089.75 | 69 | 1 |
| 23462.87305 | 69 | 1 |
![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
Run a regression of Earnings on Height.
Is the estimated slope statistically significant?
OA. Yes
OB. 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?
OA. Yes.
OB. 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 male workers only.
Is the estimated slope statistically significant?
OA. Yes
O 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)
Can you reject the null hypothesis that the effect of height on earnings is the same for men and women?
OA. Yes.
OB. No.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4eefc726-209e-41a9-acc6-2260c5292952%2F9af93750-8a64-46f9-8640-82ff049b3913%2Fpybewui_processed.png&w=3840&q=75)
Transcribed Image Text: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
Run a regression of Earnings on Height.
Is the estimated slope statistically significant?
OA. Yes
OB. 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?
OA. Yes.
OB. 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 male workers only.
Is the estimated slope statistically significant?
OA. Yes
O 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)
Can you reject the null hypothesis that the effect of height on earnings is the same for men and women?
OA. Yes.
OB. No.
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