Question #290934

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]

1
Expert's answer
2022-01-27T12:25:30-0500
xˉ1=42+39+48+60+415=46\bar{x}_1=\dfrac{42+39+48+60+41}{5}=46s12=151((4246)2+(3946)2+(4846)2s_1^2=\dfrac{1}{5-1}((42-46)^2+(39-46)^2+(48-46)^2+(6046)2+(4146)2)=1452+(60-46)^2+(41-46)^2)=\dfrac{145}{2}




s1=s12=14528.5147s_1=\sqrt{s_1^2}=\sqrt{\dfrac{145}{2}}\approx8.5147





xˉ2=38+42+48+67+405=47\bar{x}_2=\dfrac{38+42+48+67+40}{5}=47s22=151((3847)2+(4247)2+(4847)2s_2^2=\dfrac{1}{5-1}((38-47)^2+(42-47)^2+(48-47)^2+(6747)2+(4047)2)=139+(67-47)^2+(40-47)^2)=139




s2=s22=13911.7898s_2=\sqrt{s_2^2}=\sqrt{139}\approx11.7898


A F-test is used to test for the equality of variances. The following F-ratio is obtained:


F=s12s22=72.5139=0.5216F=\dfrac{s_1^2}{s_2^2}=\dfrac{72.5}{139}=0.5216

The critical values for two-tailed, df1=df2=51=4df_1=df_2=5-1=4 are FL=0.1041F_L = 0.1041  and FU=9.6045,F_U = 9.6045, and since F=0.5216,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=μ2H_0:\mu_1=\mu_2

H1:μ1μ2H_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 α=0.05,\alpha = 0.05, and the degrees of freedom are df=n1+n22=5+52=8df =n_1+n_2-2= 5+5-2=8

Hence, it is found that the critical value for this two-tailed test, α=0.05\alpha = 0.05 and df=8df = 8 is tc=2.3060.t_c = 2.3060.

The rejection region for this two-tailed test is R={t:t>2.3060}.R = \{t: |t| > 2.3060\}.

Since it is assumed that the population variances are equal, the t-statistic is computed as follows:


t=xˉ1xˉ2(n11)s12+(n21)s22n1+n22(1n1+1n2)t=\dfrac{\bar{x}_1-\bar{x}_2}{\sqrt{\dfrac{(n_1-1)s_1^2+(n_2-1)s_2^2}{n_1+n_2-2}(\dfrac{1}{n_1}+\dfrac{1}{n_2})}}

=4647(51)(72.5)+(51)(139)5+52(15+15)=\dfrac{46-47}{\sqrt{\dfrac{(5-1)(72.5)+(5-1)(139)}{5+5-2}(\dfrac{1}{5}+\dfrac{1}{5})}}

=0.153755=-0.153755

Since it is observed that t=0.1537552.3060=tc,|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=8df=8 degrees of freedom, t=0.153755,t=-0.153755, is p=0.881611,p=0.881611, and since p=0.8816110.05=α,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 μ1\mu_1 is different than μ2,\mu_2, at the α=0.05\alpha = 0.05 significance level.



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