Conduct a traditional hypothesis test for the null hypothesis H0: µ = 100 against the alternative
hypothesis H1: µ > 100 based on the 35 random observations. The sample mean is 105 and the
sample standard deviation is 15. Use α = 0.01.
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=100"
"H_1:\\mu>100"
This corresponds to a right-tailed test, for which a t-test for one mean, with unknown population standard deviation, using the sample standard deviation, will be used.
Based on the information provided, the significance level is "\\alpha = 0.01," "df=n-1=34" and the critical value for a right-tailed test is "t_c =2.44115."
The rejection region for this right-tailed test is "R = \\{t:t>2.44115\\}."
The t-statistic is computed as follows:
Since it is observed that "t=1.9720<2.44115=t_c," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach:
The p-value for right-tailed, "df=34" degrees of freedom, "t=1.9720" is "p= 0.028395," and since "p= 0.028395>0.01=\\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 100, at the "\\alpha = 0.01" significance level.
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