An electrical firm manufactures light bulb that has a length of life that is approximately normally distributed with a mean of 800 hours and a standard deviation of 40 hours. The supervising electrical Engineer took a random sample of 30 bulbs with an average life of 788 hours, test the hypothesis that µ=800 hours against the alternative hypothesis µ is greater than 800.
Use confidence level of 96%.
Is it a two tailed or one tailed test?
Null hypothesis?
Alternative hypothesis?
Size of the test?
Test statistics?
Critical region?
Decision ( accept or reject null hypothesis)?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=800"
"H_1:\\mu>800"
This corresponds to a one-tailed right-tailed test, for which a z-test for one mean, with known population standard deviation will be used.
Size of the test is "n=30."
Based on the information provided, the significance level is "\\alpha = 0.04," and the critical value for a right-tailed test is "z_c = 1.7507."
The rejection region for this right-tailed test is "R = \\{z:z>1.7507\\}."
The z-statistic is computed as follows:
Since it is observed that "z=-1.6432<1.7507=z_c," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach:
The p-value is "p=P(z>-1.6432)=0.949829," and since "p=0.949829>0.04=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu"
is greater than 800, at the "\\alpha = 0.04" significance level.
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