Xi	AVG.	HR (Yi)
1	.370	41
2	.395	49
3	.319	40
4	.326	51
5	.362	39
6	.305	45
7	.343	37
8	.347	45
9	.378	43
10	.331	47
SUMMARY OUTPUT			Y = a + bx		Y = 43.7333333333333 + (.333*-0.0121212121212125)
			a = intercept	Y =	44
Regression Statistics		b = slope
Multiple R	0.008556598
R Square	7.32154E-05
Adjusted R Square	-0.124917633
Standard Error	4.548948152
Observations	10
ANOVA
	df	SS	MS	F	Significance F
Regression	1	0.012121212	0.01212121	0.000586	0.981283811
Residual	8	165.5434343	20.6929293
Total	9	165.5555556
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	43.73333333	3.107523184	14.0733731	6.31E-07	36.56737202	50.899295	36.56737202	50.89929464
Xi	-0.012121212	0.500822709	-0.0242026	0.981284	-1.16702045	1.142778	-1.167020449	1.142778025

Baseball Averages (AVG) by the All-Star break can predict how many home runs (HR) a player will hit in a season. Given the data above n the the excel spreadsheet (Baseball), and the regression model used to predict the number of home runs of a player with an AVG of .333.

Based on the results above, is this prediction reliable? Why or why not?.