Respuesta :
Answer:
a) [tex]\S^2_p =\frac{(6-1)(1.47196)^2 +(6 -1)(4.32049)^2}{6 +6 -2}=10.417[/tex]
And the deviation would be just the square root of the variance:
[tex]S_p=3.227[/tex]
And now we can calculate the statistic:
[tex]t=\frac{(15.3333 -12.8333)-(0)}{3.227\sqrt{\frac{1}{6}+\frac{1}{6}}}=1.342[/tex]
Now we can calculate the degrees of freedom given by:
[tex]df=6+6-2=10[/tex]
And now we can calculate the p value using the altenative hypothesis:
[tex]p_v =P(t_{10}>1.342) =0.105[/tex]
If we compare the p value obtained and using the significance level assumed [tex]\alpha=0.05[/tex] we have [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis.
b) [tex] (\bar X_2 -\bar X_1) \pm t_{\alpha/2}* S_p \sqrt{\frac{1}{n_!} +\frac{1}{n_2}}[/tex]
And replacing we got:
[tex] (15.8333-12.8333) -1.812 \sqrt{\frac{1}{6} +\frac{1}{6}}= 1.954[/tex]
[tex] (15.8333-12.8333) +1.812 \sqrt{\frac{1}{6} +\frac{1}{6}}= 4.046[/tex]
Step-by-step explanation:
Part a
TYPE N MEAN STD. DEVIATION STD. ERROR MEAN
Type 1 6 12.8333 1.47196 0.60093
Type 2 6 15.3333 4.32049 1.7638
When we have two independent samples from two normal distributions with equal variances we are assuming that
[tex]\sigma^2_1 =\sigma^2_2 =\sigma^2[/tex]
And the statistic is given by this formula:
[tex]t=\frac{(\bar X_1 -\bar X_2)-(\mu_{1}-\mu_2)}{S_p\sqrt{\frac{1}{n_1}+\frac{1}{n_2}}}[/tex]
Where t follows a t distribution with [tex]n_1+n_2 -2[/tex] degrees of freedom and the pooled variance [tex]S^2_p[/tex] is given by this formula:
[tex]\S^2_p =\frac{(n_1-1)S^2_1 +(n_2 -1)S^2_2}{n_1 +n_2 -2}[/tex]
This last one is an unbiased estimator of the common variance [tex]\sigma^2[/tex]
The system of hypothesis on this case are:
Null hypothesis: [tex]\mu_2 \leq \mu_1[/tex]
Alternative hypothesis: [tex]\mu_2 > \mu_1[/tex]
Or equivalently:
Null hypothesis: [tex]\mu_2 - \mu_1 \leq 0[/tex]
Alternative hypothesis: [tex]\mu_2 -\mu_1 > 0[/tex]
Our notation on this case :
[tex]n_1 =6[/tex] represent the sample size for group 1
[tex]n_2 =5[/tex] represent the sample size for group 2
[tex]\bar X_1 =12.8333[/tex] represent the sample mean for the group 1
[tex]\bar X_2 =15.3333[/tex] represent the sample mean for the group 2
[tex]s_1= 1.47196[/tex] represent the sample standard deviation for group 1
[tex]s_2=4.32049[/tex] represent the sample standard deviation for group 2
First we can begin finding the pooled variance:
[tex]\S^2_p =\frac{(6-1)(1.47196)^2 +(6 -1)(4.32049)^2}{6 +6 -2}=10.417[/tex]
And the deviation would be just the square root of the variance:
[tex]S_p=3.227[/tex]
And now we can calculate the statistic:
[tex]t=\frac{(15.3333 -12.8333)-(0)}{3.227\sqrt{\frac{1}{6}+\frac{1}{6}}}=1.342[/tex]
Now we can calculate the degrees of freedom given by:
[tex]df=6+6-2=10[/tex]
And now we can calculate the p value using the altenative hypothesis:
[tex]p_v =P(t_{10}>1.342) =0.105[/tex]
If we compare the p value obtained and using the significance level assumed [tex]\alpha=0.05[/tex] we have [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis.
Part b
For the confidence interval we know that the confidence is 90% so then the value os [tex] \alpha = 0.1[/tex] and [tex] \alpha/2 =0.05[/tex], the degrees of freedom are given by:
[tex] df= n_1 + n_2 -2 = 6+6-2= 10[/tex]
And the crtitical value for this case would be [tex] t_{critc}= 1.812[/tex]
The confidence interval for the difference of means is given by:
[tex] (\bar X_2 -\bar X_1) \pm t_{\alpha/2}*S_p \sqrt{\frac{1}{n_!} +\frac{1}{n_2}}[/tex]
And replacing we got:
[tex] (15.8333-12.8333) -1.812 \sqrt{\frac{1}{6} +\frac{1}{6}}= 1.954[/tex]
[tex] (15.8333-12.8333) +1.812 \sqrt{\frac{1}{6} +\frac{1}{6}}= 4.046[/tex]