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, for which a t-test for two population means, with two independent samples, with unknown population standard deviations will be used.
Based on the information provided, the significance level is "\\alpha=0.05," and the degrees of freedom are "df=5+6-2." In fact, the degrees of freedom are computed as follows, assuming that the population variances are equal:
Hence, it is found that the critical value for this two-tailed test is "t_c=2.262, \\alpha=0.05, df=9."
The rejection region for this two-tailed test is "R=\\{t:|t|>2.262\\}."
Since it is assumed that the population variances are equal, the t-statistic is computed as follows:
"={7.52-7.49\\over \\sqrt{\\dfrac{(6-1)0.024^2+(5-1)0.032^2}{6+5-2}(\\dfrac{1}{6}+\\dfrac{1}{5})}}\\approx"
Since it is observed that "|t|=1.78\\leq2.262=t_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_1" is different than "\\mu_2," at the 0.05 significance level.
Using the P-value approach: The p-value is "p=0.1089," and since "p=0.1089\\geq0.05," it is then concluded that the null hypothesis is not rejected. Therefore, there is not enough evidence to claim that the population mean "\\mu_1" is different than "\\mu_2," at the 0.05 significance level.
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