The standard deviation of the number of minutes of calls of a certain subscriber is 40 min per day. A sample of 10 days gave a variance of 38 min. Test the hypothesis with α = 0.05 that the standard deviation of the call usage is not equal to 40.
The following null and alternative hypotheses need to be tested:
"H_0:\\sigma^2=1600"
"H_a:\\sigma^2\\not=1600"
This corresponds to a two-tailed test test, for which a Chi-Square test for one population variance will be used.
Based on the information provided, the significance level is "\\alpha = 0.05," "df=n-1=9" degrees of freedom and the the rejection region for this two-tailed test is "R = \\{\\chi^2: \\chi^2 < 2.7004 \\text{ or } \\chi^2 > 19.0228\\}."
The Chi-Squared statistic is computed as follows:
Since it is observed that "\\chi^2 = 0.21375<2.7004= \\chi_L^2," it is then concluded that the null hypothesis is rejected.
Therefore, there is enough evidence to claim that the population variance "\\sigma^2"
is different than 1600, at the 0.05 significance level.
Therefore, there is enough evidence to claim that the population standard deviation "\\sigma" is different than 40, at the 0.05 significance level.
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