MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Based on the results of the overall F-test, is at least one of the predictors statistically significant in predicting the total number of wins in the season? 

 

 

OLS Regression Results
Dep. Variable:
Model:
total_wins
R-squared:
Adj. R-squared:
0.837
OLS
0.837
Least Squares
Sat, 27 Feb 2021
Method:
F-statistic:
1580.
Prob (F-statistic):
Log-Likelihood:
AIC:
Date:
4.41e-243
Time:
18:17:53
-1904.6
No. Observations:
618
3815.
Df Residuals:
615
BIC:
3829.
Df Model:
2
Covariance Type:
nonrobust
coef
std err
P>|t|
[0.025
0.975]
Intercept
avg_pts
avg_elo_n
-152.5736
4.500
-33.903
0.000
-161.411
-143.736
0.3497
0.048
7.297
Θ. 000
0.256
0.444
0.1055
Θ. 002
47.952
0.000
0.101
0.110
Omnibus:
89.087
Durbin-Watson:
1.203
Prob(Omnibus):
Θ. 000
Jarque-Bera (JB):
Prob(JB):
Cond. No.
160.540
Skew:
-0.869
1.38e-35
Kurtosis:
4.793
3.19e+04
expand button
Transcribed Image Text:OLS Regression Results Dep. Variable: Model: total_wins R-squared: Adj. R-squared: 0.837 OLS 0.837 Least Squares Sat, 27 Feb 2021 Method: F-statistic: 1580. Prob (F-statistic): Log-Likelihood: AIC: Date: 4.41e-243 Time: 18:17:53 -1904.6 No. Observations: 618 3815. Df Residuals: 615 BIC: 3829. Df Model: 2 Covariance Type: nonrobust coef std err P>|t| [0.025 0.975] Intercept avg_pts avg_elo_n -152.5736 4.500 -33.903 0.000 -161.411 -143.736 0.3497 0.048 7.297 Θ. 000 0.256 0.444 0.1055 Θ. 002 47.952 0.000 0.101 0.110 Omnibus: 89.087 Durbin-Watson: 1.203 Prob(Omnibus): Θ. 000 Jarque-Bera (JB): Prob(JB): Cond. No. 160.540 Skew: -0.869 1.38e-35 Kurtosis: 4.793 3.19e+04
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