Question: 1) Use the python statistical data to answer the questions below: OLS Regression Results ============================================================================== Dep. Variable: total_wins R-squared: 0.823 Model: OLS Adj. R-squared: 0.823

1) Use the python statistical data to answer the questions below:

OLS Regression Results ============================================================================== Dep. Variable: total_wins R-squared: 0.823

Model: OLS Adj. R-squared: 0.823

Method: Least Squares F-statistic: 2865.

Date: Tue, 14 Feb 2023 Prob (F-statistic): 8.06e-234

Time: 04:17:05 Log-Likelihood: -1930.3

No. Observations: 618 AIC: 3865.

Df Residuals: 616 BIC: 3873.

Df Model: 1

Covariance Type: nonrobust ============================================================================== coef std err t P>|t| [0.025 0.975]

------------------------------------------------------------------------------

Intercept -128.2475 3.149 -40.731 0.000 -134.431 -122.064

avg_elo_n 0.1121 0.002 53.523 0.000 0.108 0.116 ============================================================================== Omnibus: 152.822 Durbin-Watson: 1.098

Prob(Omnibus): 0.000 Jarque-Bera (JB): 393.223

Skew: -1.247 Prob(JB): 4.10e-86

Kurtosis: 6.009 Cond. No. 2.14e+04 ==============================================================================

a. With a level of significance of 0.01, what is the Test Statistic and P-value? Identify a null hypothesis and alternative hypothesis. What is the conclusion of the hypothesis test and its interpretation based on the P-value?

b. Based on the results of the overall F-test, can average relative skill predict the total number of wins in the regular season?

c. 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.

d. What is the predicted number of wins in a regular season for a team that has an average relative skill of 1450? Round your answer down to the nearest integer.

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