a coffe manufacturer is interested in whether the mean daily consumption of regular coffee drinkers decaffeinated coffee . a random sample of 50 regular coffee drinkers showed a mean of 4.35 cups per day . a sample of 40 decaffeinated coffee drinkers showed a mean of 5.84 cups a day. use the .01 significance level. compute the p-value .
The following null and alternative hypotheses need to be tested:
"H_0:\\mu_1\\ge\\mu_2"
"H_a:\\mu_1<\\mu_2"
This corresponds to a left-tailed test, and a z-test for two means, with known population standard deviations will be used.
Based on the information provided, the significance level is "\\alpha = 0.01," and the critical value for a left-tailed test is "z_c = -2.3263."
The rejection region for this left-tailed test is"R = \\{z: z < -2.3263\\}."
The z-statistic is computed as follows:
"=\\dfrac{4.35-5.84}{\\sqrt{(1.2)^2\/50+(1.36)^2\/40}}=-5.4393"
Using the P-value approach:
The p-value is "p=P(Z<-5.4393)=0.00000002," and since "p=0.00000002<0.01=\\alpha," it is concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population mean "\\mu_1"
is less than "\\mu_2," at the "\\alpha = 0.01" significance level.
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