An association of City Mayors conducted a study to determine the average number of times
a family went to buy necessities in a week. They found that the mean is 4 times in a week. A
random sample of 20 families were asked and found a mean of 5 times in a week and a
standard deviation of 2. Use 5% significance level to test that the population mean is not
equal to 4. Assume that the population is normally distributed.
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=4"
"H_a:\\mu\\not=4"
This corresponds to a two-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 = 0.05," "df=n-1=19" degrees of freedom, and the critical value for a two-tailed test is "t_c = 2.093024."
The rejection region for this two-tailed test is "R = \\{t: |t| > 2.093024\\}."
The t-statistic is computed as follows:
Since it is observed that "|t| = 2.236068 >2.093024=t_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach:
The p-value for two-tailed, "df=19" degrees of freedom, "t=2.236068" is "p=0.037541," and since "p=0.037541<0.05=\\alpha," it is concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population mean "\\mu" is different than 4, at the "\\alpha = 0.05" significance level.
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