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?