A group of 5 patients treated with Medicine type A weight 42, 39, 48, 60 and 41 kg.
A second group of 5 patients treated with Medicine type B weight 38, 42, 48, 67, 40 kg. Do
the two medicines differ significantly with regard to their effect and increasing weight? [At
5% level of significance]
A F-test is used to test for the equality of variances. The following F-ratio is obtained:
The critical values for two-tailed, "df_1=df_2=5-1=4" are "F_L = 0.1041" and "F_U = 9.6045," and since "F = 0.5216," then the null hypothesis of equal variances is not rejected.
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.
The significance level is "\\alpha = 0.05," and the degrees of freedom are "df =n_1+n_2-2= 5+5-2=8"
Hence, it is found that the critical value for this two-tailed test, "\\alpha = 0.05" and "df = 8" is "t_c = 2.3060."
The rejection region for this two-tailed test is "R = \\{t: |t| > 2.3060\\}."
Since it is assumed that the population variances are equal, the t-statistic is computed as follows:
"=\\dfrac{46-47}{\\sqrt{\\dfrac{(5-1)(72.5)+(5-1)(139)}{5+5-2}(\\dfrac{1}{5}+\\dfrac{1}{5})}}"
"=-0.153755"
Since it is observed that "|t| = 0.153755 \\le 2.3060=t_c ," it is then concluded that the null hypothesis is not rejected.
Using the P-value approach:
The p-value for two-tailed, "df=8" degrees of freedom, "t=-0.153755," is "p=0.881611," and since "p = 0.881611 \\ge 0.05=\\alpha," it is concluded that the null hypothes is not rejected.
Therefore, there is not enough evidence to claim that the population mean "\\mu_1" is different than "\\mu_2," at the "\\alpha = 0.05" significance level.
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