•Based on the results of the overall F-test, can average relative skill predict the total number of wins in the regular season? •What is the predicted total number of wins in a regular season for a team that has an average relative skill of 1550? Round your answer down to the nearest integer. •What is the predicted number of wins in a regular season for a team that has an average relative skill of 14507 Round your answer down to the nearest integer.
•Based on the results of the overall F-test, can average relative skill predict the total number of wins in the regular season? •What is the predicted total number of wins in a regular season for a team that has an average relative skill of 1550? Round your answer down to the nearest integer. •What is the predicted number of wins in a regular season for a team that has an average relative skill of 14507 Round your answer down to the nearest integer.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
•Based on the results of the overall F-test, can average relative skill predict the total number of wins in the regular season?
•What is the predicted total number of wins in a regular season for a team that has an average relative skill of 1550? Round your answer down to the nearest integer.
•What is the predicted number of wins in a regular season for a team that has an average relative skill of 14507 Round your answer down to the nearest integer.
![Dep. Variable:
Model:
Method:
Date:
Time:
No. Observations:
Df Residuals:
Df Model:
Covariance Type:
coef
Omnibus:
Prob (Omnibus):
Skew:
Kurtosis:
Intercept -128.2475
avg_elo_n
0.1121
OLS Regression Results
total_wins
OLS
Least Squares
Fri, 13 Oct 2023
09:37:26
nonrobust
std err
618
616
1
3.149
0.002
R-squared:
Adj. R-squared:
Prob (F-statistic):
152.822
0.000
-1.247
6.009
F-statistic:
Log-Likelihood:
AIC:
BIC:
t
-40.731
53.523
P>|t|
0.000
0.000
Durbin-Watson:
Jarque-Bera (JB):
Prob (JB):
Cond. No.
[0.025
-134.431
0.108
0.823
0.823
2865.
8.06e-234
-1930.3
3865.
3873.
0.975]
-122.064
0.116
1.098
393.223
4.10e-86
2.14e+04](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9d62d096-051c-4718-a327-e350c164712e%2Ff1ca2d92-5676-43a0-94f0-64f53d554d69%2Fmhhpfd4_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Dep. Variable:
Model:
Method:
Date:
Time:
No. Observations:
Df Residuals:
Df Model:
Covariance Type:
coef
Omnibus:
Prob (Omnibus):
Skew:
Kurtosis:
Intercept -128.2475
avg_elo_n
0.1121
OLS Regression Results
total_wins
OLS
Least Squares
Fri, 13 Oct 2023
09:37:26
nonrobust
std err
618
616
1
3.149
0.002
R-squared:
Adj. R-squared:
Prob (F-statistic):
152.822
0.000
-1.247
6.009
F-statistic:
Log-Likelihood:
AIC:
BIC:
t
-40.731
53.523
P>|t|
0.000
0.000
Durbin-Watson:
Jarque-Bera (JB):
Prob (JB):
Cond. No.
[0.025
-134.431
0.108
0.823
0.823
2865.
8.06e-234
-1930.3
3865.
3873.
0.975]
-122.064
0.116
1.098
393.223
4.10e-86
2.14e+04
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