A F-test is used to test for the equality of variances. The following F-ratio is obtained:
F=s22s12=13972.5=0.5216
The critical values for two-tailed, df1=df2=5−1=4 are FL=0.1041 and FU=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:
H0:μ1=μ2
H1:μ1=μ2
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 α=0.05, and the degrees of freedom are df=n1+n2−2=5+5−2=8
Hence, it is found that the critical value for this two-tailed test, α=0.05 and df=8 is tc=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:
Since it is observed that ∣t∣=0.153755≤2.3060=tc, 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≥0.05=α, it is concluded that the null hypothes is not rejected.
Therefore, there is not enough evidence to claim that the population mean μ1 is different than μ2, at the α=0.05 significance level.
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