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 5. Assume that the population is normally distributed. What should be the decision for the hypothesis?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=5"
"H_1:\\mu\\not=5"
This corresponds to a two-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 two-tailed test is "z_c = 1.96."
The rejection region for this two-tailed test is "R = \\{z:|z|>1.96\\}."
The z-statistic is computed as follows:
Since it is observed that "|z|=0<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=2P(z<0)= 1," and since "p= 1>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 different than 5, at the "\\alpha = 0.05" significance level.
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