A mathematics teacher in senior high school developed a problem-solving test to randomly selected 40 grade 11 students. These students had an average score of 85 and a standard deviation of 5. If the population had a mean score of 90 and a standard deviation of 3, use 5% level of significance to test the hypothesis.
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=90"
"H_1:\\mu\\not=90"
This corresponds to a two-tailed test, for which a z-test for one mean, with known population standard deviation will be used.
Based on the information provided, the significance level is "\\alpha = 0.05," and the critical value for a two-tailed test is "z_c = 1.96."
The rejection region for this two-tailed test is "R = \\{z: |z| > 1.96\\}."
The z-statistic is computed as follows:
Since it is observed that "|z| = 10.541 > 1.96=z_c," it is then concluded that the null hypothesis is rejected.
Using the P-value approach: The p-value is "p=2P(z<-10.541)\\approx0," and since "p=0<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 90, at the "\\alpha = 0.05" significance level.
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