A company that produces batteries claims that the life expectancy of their batteries is 90 hours with a standard deviation of 10 hours. A consumer interest group believes that the actual battery life expectancy of these batteries is shorter than the claimed battery life. In order to prove this, they test a random sample of 20 batteries which resulted a mean of 87 hours. Conduct a hypothesis test with a significance level of 0.05
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=90"
"H_a:\\mu<90"
This corresponds to a left-tailed test, for which a z-test for one mean, with known population standard deviation will be used.
Based on the information provided, the significance level is "\\alpha = 0.05," and the critical value for a left-tailed test is "z_c = -1.6449."
The rejection region for this left-tailed test is "R = \\{z: z < -1.6449\\}."
The z-statistic is computed as follows:
Since it is observed that "z = -1.34164>-1.6449= 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<-1.34164)=0.089856," and since "p=0.089856>0.05=\\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 less than 90, at the "\\alpha = 0.05" significance level.
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