A tobacco company advertises that the average nicotine content of its cigarettes is at
most 14 milligrams. A consumer protection agency wants to determine whether the
average nicotine content is in fact greater than 14. A random sample of 300 cigarettes
of the company’s brand yield an average nicotine content of 14.6 and a standard
deviation of 3.8 milligrams. Determine the level of significance of the statistical test of
the agency’s claim that 𝜇 is greater than 14. If 𝛼 = 0.01, is there significant evidence
that the agency’s claim has been supported by the data?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\leq 14"
"H_1:\\mu>14"
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=299" degrees of freedom, and the critical value for a right-tailed test is "t_c =2.338884."
The rejection region for this right-tailed test is "R = \\{t: t > 2.338884.\\}"
The t-statistic is computed as follows:
"\\approx 2.734817"
Since it is observed that "t = 2.734817>2.338884 = t_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach: The p-value for right-tailed, "\\alpha=0.01, df=299" degrees of freedom, "t=2.734817" is"p=0.003307," and since "p=0.003307<0.01=\\alpha," it is concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population mean "\\mu"
is greater than 14, at the "\\alpha = 0.01" significance level.
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