For the past few years, the number of customers of a drive-in bottle shop has averaged 20 per hour. This year, another bottle shop one kilometre away opened a drive-in window. The manager of the first shop believes that this will result in a decrease in customers. A random sample of 50 hours showed an average of 18.7 customers per hour with a standard deviation of 3.0. Can we conclude at the 5% level of significance that the manager’s belief is correct?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\geq20"
"H_1:\\mu<20"
This corresponds to a left-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," and the critical value for a left-tailed test for "\\alpha=0.05" and "df=n-1=50-1=49" degrees of freedom is "t_c=-1.676551." The rejection region for this left-tailed test is "R=\\{t: t<-1.676551\\}."
The t-statistic is computed as follows:
Since it is observed that "t=-3.064129< -1.676551=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 less than 20, at the "\\alpha=0.05" significance level.
Using the P-value approach: The p-value for left-tailed, "t=-3.064129, df=49," "\\alpha=0.05" is "p=0.001772," and since "p=0.001772<0.05," it is concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population mean "\\mu" is less than 20, at the "\\alpha=0.05" significance level.
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