Two methods of teaching statistics are being tried by a professor. A class of 40 students is taught by method A and a class of 36 is taught by method B. the two classes are given the same final examination. The scores are: Using the .01 significance level, can we conclude that the average final examination scores produced by the two methods are different if the population standard deviation is 5?
The following null and alternative hypotheses need to be tested:
"H_0:\\mu_1=\\mu_2"
"H_1:\\mu_1\\not=\\mu_2"
This corresponds to a two-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 two-tailed test is "z_c = 2.5758."
The rejection region for this two-tailed test is "R = \\{z: |z| > 2.5758\\}."
The z-statistic is computed as follows:
Since it is observed that "|z| = 3.4823 >2.5758= z_c ," it is then concluded that the null hypothesis is rejected.
Using the P-value approach:
The p-value is "p=2P(z>3.4823)=0.000497," and since
"p = 0.000497 < 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 different than "\\mu_2," at the "\\alpha = 0.01" significance level.
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