Investigating a complaint from a buyer that there is short-weight selling, a manufacturer takes a random sample of twenty-five 32 g cans of coffee from a large shipment and finds that the mean weight is 31 g with a standard deviation of 0.6 g. Is there evidence of short-weighing at the 0.01 level significance?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu\\ge32"
"H_a:\\mu<32"
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 = 0.01," "df=n-1=34" degrees of freedom, and the critical value for a left-tailed test is "t_c = -2.44115."
The rejection region for this left-tailed test is "R = \\{t: t<-2.44115\\}."
The t-statistic is computed as follows:
Since it is observed that "t=-9.8601< -2.44115=t_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach:
The p-value for left-tailed, "df=34" degrees of freedom, "t=-9.8601" is "p=0," and since "p=0<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 less than 32, at the "\\alpha = 0.01" significance level.
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