Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables ● margin, the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: . regress margin home if team== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 MS 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 t Number of obs F(1, 80) Prob > F R-squared. Adj R-squared Root MSE P>|t| 2.77 0.007 -2.42 0.018 2.370137 -9.510864 = = = [95% Conf. Interval] The Nets average margin of victory for all games in 2014 was positive The Nets average margin of victory for all games in 2014 was negative The Nets won more games than they lost in 2014 The Nets lost more games than they won in 2014 None of the above 82 7.66 0.0070 0.0874 0.0760 13.808 14.50791 -.9281607 This output tells us the regression line equation is: margin: = -5.2 +8.4home. Assuming that the Nets played half of their games at home and half away, which of the following conclusions can we make with certainty from the regression results? (check all that apply)
Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables ● margin, the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: . regress margin home if team== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 MS 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 t Number of obs F(1, 80) Prob > F R-squared. Adj R-squared Root MSE P>|t| 2.77 0.007 -2.42 0.018 2.370137 -9.510864 = = = [95% Conf. Interval] The Nets average margin of victory for all games in 2014 was positive The Nets average margin of victory for all games in 2014 was negative The Nets won more games than they lost in 2014 The Nets lost more games than they won in 2014 None of the above 82 7.66 0.0070 0.0874 0.0760 13.808 14.50791 -.9281607 This output tells us the regression line equation is: margin: = -5.2 +8.4home. Assuming that the Nets played half of their games at home and half away, which of the following conclusions can we make with certainty from the regression results? (check all that apply)
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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Question
![Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables
- \( \text{margin}_i \) - the Net’s margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game \( i \), and
- \( \text{home}_i \) - a dummy variable equal to 1 when the Nets are the home team (game \( i \) was played in their home arena) and equal to 0 when they are the away team (game \( i \) was played in the opponent’s arena).
I use the least-squares method to estimate the following regression model
\[ \text{margin}_i = \alpha + \beta \text{home}_i + e_i \]
Below is the Stata output corresponding to the estimated regression line:
```
. regress margin home if team == "Brooklyn Nets"
Source SS df MS Number of obs = 82
F(1, 80) = 7.66
Model 1459.95122 1 1459.95122 Prob > F = 0.0070
Residual 15252.0488 80 190.65061 R-squared = 0.0874
Adj R-squared = 0.0760
Total 16712 81 206.320988 Root MSE = 13.808
-------------------------------------------------------------------------------
margin Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------------------------------------------------------------------------
home 8.439024 3.045959 2.77 0.007 2.370137 14.50791
_cons -5.219512 2.156389 -2.42 0.018 -9.510864 -0.9281603
-------------------------------------------------------------------------------
```
This output tells us the regression line equation is:
\[ \hat{\text{margin}} = -5.2 + 8.4 \text{home} \]
Assuming that the Nets played half of their games at home and half away, which of the following conclusions can we make with certainty from the regression results? (check all that apply)
- [ ] The Nets average margin of](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3f08d3cb-03f2-44ac-afec-90ed33ecc605%2Fe3fb7aab-68d2-4e5e-9afd-8cb5ba5cd0e9%2Fzivfni_processed.png&w=3840&q=75)
Transcribed Image Text:Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables
- \( \text{margin}_i \) - the Net’s margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game \( i \), and
- \( \text{home}_i \) - a dummy variable equal to 1 when the Nets are the home team (game \( i \) was played in their home arena) and equal to 0 when they are the away team (game \( i \) was played in the opponent’s arena).
I use the least-squares method to estimate the following regression model
\[ \text{margin}_i = \alpha + \beta \text{home}_i + e_i \]
Below is the Stata output corresponding to the estimated regression line:
```
. regress margin home if team == "Brooklyn Nets"
Source SS df MS Number of obs = 82
F(1, 80) = 7.66
Model 1459.95122 1 1459.95122 Prob > F = 0.0070
Residual 15252.0488 80 190.65061 R-squared = 0.0874
Adj R-squared = 0.0760
Total 16712 81 206.320988 Root MSE = 13.808
-------------------------------------------------------------------------------
margin Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------------------------------------------------------------------------
home 8.439024 3.045959 2.77 0.007 2.370137 14.50791
_cons -5.219512 2.156389 -2.42 0.018 -9.510864 -0.9281603
-------------------------------------------------------------------------------
```
This output tells us the regression line equation is:
\[ \hat{\text{margin}} = -5.2 + 8.4 \text{home} \]
Assuming that the Nets played half of their games at home and half away, which of the following conclusions can we make with certainty from the regression results? (check all that apply)
- [ ] The Nets average margin of
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