Answer to Question #303516 in Statistics and Probability for venkat

Question #303516

Two independent samples of sizes 8 and 7 contained the following values:


Sample I : 19 17 15 21 16 18 16 14


Sample II : 16 14 15 19 15 18 16


Do the estimates of the population variance differ significantly at 5% level?

1
Expert's answer
2022-02-28T14:15:18-0500
"s^2=\\dfrac{\\sum_i(x_i-\\bar{x})^2}{n-1}"


"\\bar{x}_1=\\dfrac{19+ 17+ 15 +21+ 16+ 18 +16 +14}{8}=17"

"s_1^2=\\dfrac{\\sum_i(x_i-17)^2}{8-1}=5.142857"



"\\bar{x}_2=\\dfrac{16 +14 +15 +19+ 15 +18 +16}{7}=\\dfrac{113}{7}"

"s_2^2=\\dfrac{\\sum_i(x_i-\\dfrac{113}{7})^2}{7-1}=3.142857"

The following null and alternative hypotheses need to be tested:

"H_0:\\sigma_1^2=\\sigma_2^2"

"H_1:\\sigma_1^2\\not=\\sigma_2^2"

This corresponds to a two-tailed test, for which a F-test for two population variances needs to be used.

Based on the information provided, the significance level is "\\alpha = 0.05," "df_1=8-1=7, df_2=7-1=6" degrees of freedom, and the the rejection region for this two-tailed test test is 

"R = \\{F: F < 0.1954 \\text{ or } F > 5.6955\\}"


The F-statistic is computed as follows:


"F=\\dfrac{s_2^2}{s_1^2}=\\dfrac{5.142857}{3.142857}=1.6363"

Since from the sample information we get that

"F_L=0.1954\\le F=1.6363\\le5.6955=F_R,"


it is then concluded that the null hypothesis is not rejected.

Therefore, there is not enough evidence to claim that the population variance "\\sigma_1^2"  is different than the population variance "\\sigma_2^2," at the "\\alpha = 0.05" significance level.


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