Consider the following ten IQ scores. IQ test scores are scaled to have
a mean of 100 and a standard deviation of 15.
65 98 103 77 93 102 102 113 80 94
Test the hypothesis that the mean is 100.
"=\\dfrac{927}{10}=92.7"
"\\sigma=15"
The provided sample mean is "\\bar{x}=92.7" and the known population standard deviation is "\\sigma=15," and the sample size is "n=10."
The following null and alternative hypotheses need to be tested:
"H_0:\\mu=100"
"H_1:\\mu\\not=100"
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|=1.539<1.96=z_c," it is then concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu" is different than 100, at the 0.05 significance level.
Using the P-value approach: The p-value is "p=2P(z<-1.539)=0.123804," and since "p=0.123804>0.05=\\alpha," it is concluded that the null hypothesis is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu" is different than 100, at the 0.05 significance level.
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