Regression. A coach wants to see the relationship between the statistics of practice games and official games of a local

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Regression. A coach wants to see the relationship between the statistics of practice games and official games of a local soccer team. A sample of 13 players was used and the resulting (partia) Excel output is shown below. Aasume both and y form normal distributions Regression Multiple R R Square Adjusted R Square Standard Efor Observations Static 0.70524 0.668396 6.700633 13 Coefficients Standard Stat Prove Lower Upper
Regression Multiple R R Square Adjusted R Square Standard Error Observations Intercept Midterm Statistics *** 0.70524 0.668395 8.703633 13 Coefficients Standard Error t Stał P-value Lower 95% 4.794266 0.001366 21.1673 40.2132 8.506861 0.741388 0.178042 4.377843 0.002365 0.362046 Upper 95% 60.40101 1.169078
(a) The slope of the regression line is OA. 0.178 OB. 4.378 OC. 0.741 OD. 40.213
(b) The correlation coefficient is OA. None of the other answers B. 0.705 OC. 0.8398 OD. -0.8398 A hypothesis test is done to determine whether the correlation coefficient is significantly different from zero.
(c) The alternate hypothesis is OA. H₁ :p # 0 OB. H₁ : ß # 0 OC. H₁: p = 0 OD. H₁ : μ = 0
(d) The test statistic is OA. 4.794 OB. None of the other answers OC. 40.78 OD. 0.362
(e) The degrees of freedom are: OA. 13 OB. 10 C. 11 OD. 12
(f) At the 5% significance level it can be concluded that there is evidence to suggest the correlation coefficient is OA. not zero OB. zero C. positive D. negative