A soda manufacturer is interested in determining wheter its bottling machine tends to overfill. Each bottle is supposed to contain 12 ounces of fluid. A random sample of 25 bottles was taken and found that the mean amount of soda of the sample of bottles is 12.2 ounces with a standard deviation of 0.4 ounces. If the manufacturer decides on a significance level of 0.05 test, should the null hypothesis (u=12 ounces) be rejected?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=12"
"H_1:\\mu\\not=12"
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=24" and the critical value for a two-tailed test is "t_c = 2.063899."
The rejection region for this two-tailed test is "R = \\{t:|t|>2.063899\\}."
The t-statistic is computed as follows:
Since it is observed that "|t|=2.5> 2.063899=t_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach:
The p-value for two-tailed, "df=24" degrees of freedom, "t=2.5" is "p= 0.019654," and since "p= 0.019654<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 12, at the "\\alpha = 0.05" significance level.
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