Suppose a financial analyst wants to determine whether to change all the light bulbs at Yankee Stadium or change them one by one as they burn out. There are two brands of bulbs that can be used. Because both the mean and the variance of the lengths of life are important, it was decided to test the two brands. A random sample of both brands are drawn and left on until they burned out. The times were recorded. Can the Yankee Stadium management conclude that the variances differ at 5% level of significance?

Suppose a financial analyst wants to determine whether to change all the light bulbs at Yankee Stadium or change them one by one as they burn out. There are two brands of bulbs that can be used. Because both the mean and the variance of the lengths of life are important, it was decided to test the two brands. A random sample of both brands are drawn and left on until they burned out. The times were recorded. Can the Yankee Stadium management conclude that the variances differ at 5% level of significance?

F-Test Two-Sample for Variances
	Brand A	Brand B
Mean	2504.26	2455.25
Variance	41308.881	19849.745
Observations	100	100
df	99	99
F	2.0810787
P(F<=f) one-tail	0.0001607
F Critical one-tail	1.3940613

		There is enough evidence to conclude that the variances differ because the p-value is 0.0001607 which is less than 5%.
		There is enough evidence to conclude that the variances differ because the p-value is 0.0003 which is less than 5%.
		There is not enough evidence to conclude that the variances differ because the p-value is 0.0001607 which is less than 5%.
		There is not enough evidence to conclude that the variances differ because the p-value is 0.0003 which is less than 5%.