Below is the output from a simple linear regression equation

1.         Below is the output from a simple linear regression equation analysis of this year’s NCAA men’s basketball tournament (last March).  It is an attempt to predict the score that the winning team has based on the number of victories that it had prior to the game for which the score was recorded. (Several columns in the last section have been eliminated for ease. SUMMARY OUTPUT Regression Statistics Multiple R 0.154225 R Square 0.023785 Adjusted R 0.007515 Standard Error 9.8585 Observations Left blank intentionally ANOVA df SS MS F Significant F Regression 1 142.08 142.08 1.462 0.231 Residual 60 5831.40 97.19 Total 61 5973.48 Coefficients Standard Error t-stat p-value Lower 95% Upper 95% Intercept 86.70 10.97 7.90 7.26E-11 64.75 108.65 Wins -0.488 0.404 -1.21 0.231 -1.30 0.32             a.         (6)        What is the estimated regression equation?             b.         (5)        Is the regression equation statistically significant?  How do you know?             c.         (4)        How many observations are there in this sample?             d.         (5)        If the team had won 30 games, what would your estimate of their score be? e.         (5)        How much of the variation in the dependent variable is “explained” by the independent variable?