Mean life time of a sample of 400 of an product by a company is 1600 hours with a standard deviation of 150 hours. Test the hypothesis that the mean life of the product is more than 1570 hours at 1% level of significance
The provided sample mean is "\\bar{x}=1600" and the sample standard deviation is "s=150,"
and the sample size is "n=400."
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\leq1570"
"H_1:\\mu>1570"
This corresponds to a right-tailed test, for which a t-test for one mean, with unknown population standard deviation will be used.
Based on the information provided, the significance level is "\\alpha=0.01," the number of degrees of freedom are "df=n-1=400-1=399," and the critical value for a right-tailed test is "t_c=2.33573."
The rejection region for this right-tailed test is "R=\\{t:|t|>2.33573\\}."
The t-statistic is computed as follows:
Since it is observed that "t=4>2.33573=t_c," it is then concluded that the null hypothesis is rejected. Therefore, there is enough evidence to claim that the population mean "\\mu" is greater than 1570, at the 1% significance level.
Using the P-value approach:
The p-value for "t=4, df=399, \\alpha=0.01, right-tailed" is "p=0.000038," and since "p=0.00003<0.01=\\alpha," it is then concluded that the null hypothesis is rejected. Therefore, there is enough evidence to claim that the population mean "\\mu" is greater than 1570, at the 1% significance level.
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