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

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Regression A Coach Wants To See The Relationship Between The Statistics Of Practice Games And Official Games Of A Local 1
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Regression A Coach Wants To See The Relationship Between The Statistics Of Practice Games And Official Games Of A Local 2
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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 22 players was used and the resulting (partial) Excel output is shown below. Assume both x and y form normal distributions. Regression Multiple R R Square Adjusted R Square Standard Error Observations Intercept Midterm Statistics 0.70524 0.668395 8.703633 22 Coefficients Standard t Stat Error 40.87128 8.506861 0.708148 0.17279 (a) The slope of the regression line is O A. 40.871 OB. 4.379 OC. 0.708 OD. 0.173 (b) The correlation coefficient is OA. None of the other answers B. 0.8398 OC. 0.705 OD. -0.8398 P-value Lower 95% 4.794266 0.001366 21.1673 4.378895 0.002365 0.362046 Upper 95% 60.40101 1.169078 C
A hypothesis test is done to determine whether the correlation coefficient is significantly different from zero. (c) The alternate hypothesis is O A. H₁ : ß # 0 1 B. H₁ μ = 0 C. H₁ : p = 0 O D. H₁ :p # 0
(d) The test statistic is O A. 4.794 OB. 40.78 O C. 0.362 O D. None of the other answers (e) The degrees of freedom are: O A. 19 O B. 22 O C. 21 O D. 20
(f) At the 5% significance level it can be concluded that there is evidence to suggest the correlation coefficient is A. zero B. not zero C. positive D. negative
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