You are given the following information of a company that produces cola fizzy drinks. The
company states that the mean caffeine content per bottle of a fizzy drink is 40 mg with a
standard deviation of 7.5 mg. The quality controller is convinced that it is lower. A sample of
30 randomly drawn bottles has a mean caffeine content of 39.2 mg. Can the quality
controller reject the claim? Conduct a hypothesis test at 0.05 level of significance.
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\ge40"
"H_1:\\mu<40"
This corresponds to a left-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 left-tailed test is "z_c = -1.6449."
The rejection region for this left-tailed test is "R = \\{z:z<-1.6449\\}."
The z-statistic is computed as follows:
Since it is observed that "z=-0.5842>-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=P(z<-0.5842)= 0.279543," and since "p= 0.279543>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 less than 40, at the "\\alpha = 0.05" significance level.
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