Oh my. I am completely lost. Any guidance you can give me would be appreciated. I think I know the p-value and that's all.

111e data will be aggregated to calculate the number of wins for teams in a basketball regular season between the years 1995 and 2015. ynuu tranilu \"mm awioppim: amicloin :vloppiuloin awipujlmnnual awiliojimmntlal 101.1me 0 1995 Bucks 99 3-11-1153 103107317 1363 SCI-1739 1191311587 1 36585-1 -12B T136798 3-1 1 1995 Bulls 101 52-1390 '35 69.512? 1569 892129 1135199352 I 829268 51692??? .1? 2 1995 Cavalieis 90 451220 59629265 1542 433391 1496546261 5521951 43.55.5110 43 :1 1955 Celtics 1023130455 1016511537 1-131301532 1155.93622-1 4.1318049 4345251393 35 d 1995 Clippers 96 6mm 105 E29263 1:109 053701 1511260260 3153537 -203 206558 1? printed only the first Five observations... 'lumber' of rows in the dataset - E113 Scatterle and Correlation for the Total Number of Wins and Average Relative Skill Total Number of Wins by Average Relative Skill Total Number of Wll'lS 1 1 1 1 1 1400 1500 1600 HUD 1800 Average Relative Skill 1 1300 Correlation between Average Relative Skill and the Total Number of l-lins Pearson Correlation Coefficient Pvalue 8.98?2 6.6 The ooach of your team suggests a simple linear regression model with the total number of wins as the response variable and the average relative skill as the predictor variable. He expects a team to have more wins in a season it it maintains a high average relative skill during that season. This regression model will help your coach predict how many games your team might win in a regular season. Create this simple linear regression model. Predicting die Total Number of Wins using Average Relative Skill 0L5 Regression Results Dep. variable tota1_11ins R-squared 8.823 Model: 0L5 Adj. Rsquared: 8.823 Method: Least Squares F-statistic: 2865. Date: Tue, 11 Oct 2622 Prob (F-statistic): 8.86e-234 Time: 66:39:52 Log-Likelihood: 4935.3 No. Observations: 615 art: 3865. of Residuals: 516 SIC: 3373. of Model: 1 (ovariance Type: nonrobust coef std err t p>|t| [8.825 6.975] Intercept 428.2425 3.149 416.231 6.666 4.34.431 422.064 avg elo_n 8.1121 8.882 53.523 6.883 9.183 8.115 Omnibus: 152.322 Durbin-Natson: 1.993 Prob(0nnibus): 9.8613 JarqueBera (38): 393.223 Skew: 4.2-1? ProbUB): 4.1ee86 Kurtosi 6.869 Cond. No. Warnings: [1] Standard Errors assume that the covariance matrix oi: the errors is correctly specified [2] The condition number is large, 24591-811. This might. indicate that there are strong multicollinearity or other numerical problems. What is the equation for your model? Null Hypothesis and alternative hypothesis [statistical notation and in words}? Level of Signicance? What are the results of the overall F-test? Test Statistic? Pvalue? Conclusion of the hypothesis test and its interpretation based on the Pvalue? 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 1450? Round your answer down to the nearest integer