Respuesta :
Answer:
a) If we see the alternative hypothesis we see that we are conducting a bilateral test or two tail.
b) (-1.9886, 1.9886)
c) [tex]t=\frac{(100 -98.4)-(0)}{\sqrt{\frac{3.4^2}{41}}+\frac{5.6^2}{45}}=1.617[/tex]
d) [tex]p_v =2*P(t_{84}>1.617) =0.1096[/tex]
So with the p value obtained and using the significance level given [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, and we can said that at 5% of significance the mean of the group 1 is NOT significantly different than the mean for the group 2.
e) [tex]p_v =2*P(t_{84}>1.617) =0.1096[/tex]
We can use the following excel code to calculate it: "=2*(1-T.DIST(1.617;84;TRUE))"
Step-by-step explanation:
The system of hypothesis on this case are:
Null hypothesis: [tex]\mu_1 = \mu_2[/tex]
Alternative hypothesis: [tex]\mu_1 \neq \mu_2[/tex]
Or equivalently:
Null hypothesis: [tex]\mu_1 - \mu_2 = 0[/tex]
Alternative hypothesis: [tex]\mu_1 -\mu_2\neq 0[/tex]
Our notation on this case :
[tex]n_1 =41[/tex] represent the sample size for group 1
[tex]n_2 =45[/tex] represent the sample size for group 2
[tex]\bar X_1 =100[/tex] represent the sample mean for the group 1
[tex]\bar X_2 =98.4[/tex] represent the sample mean for the group 2
[tex]s_1=3.4[/tex] represent the sample standard deviation for group 1
[tex]s_2=5.6[/tex] represent the sample standard deviation for group 2
Part a
If we see the alternative hypothesis we see that we are conducting a bilateral test or two tail.
Part b
On this case since the significance level is 0.05 and we are conducting a bilateral test we have two critical values, and we need on each tail of the distribution [tex]\alpha/2 = 0.025[/tex] of the area.
The distribution on this cas since we don't know the population deviation for both samples is the t distribution with [tex]df=n_1+n_2 -2= 41+45-2=84[/tex] degrees of freedom.
We can use the following excel codes in order to find the critical values:
"=T.INV(0.025,84)", "=T.INV(1-0.025,84)"
And we got: (-1.9886, 1.9886)
Part c
The statistic is given by this formula:
[tex]t=\frac{(\bar X_1 -\bar X_2)-(\mu_{1}-\mu_2)}{\sqrt{\frac{s^2_1}{n_1}}+\frac{S^2_2}{n_2}}[/tex]
And now we can calculate the statistic:
[tex]t=\frac{(100 -98.4)-(0)}{\sqrt{\frac{3.4^2}{41}}+\frac{5.6^2}{45}}=1.617[/tex]
The degrees of freedom are given by:
[tex]df=41+45-2=84[/tex]
Part d
And now we can calculate the p value using the altenative hypothesis:
[tex]p_v =2*P(t_{84}>1.617) =0.1096[/tex]
So with the p value obtained and using the significance level given [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, and we can said that at 5% of significance the mean of the group 1 is NOT significantly different than the mean for the group 2.
Part e
[tex]p_v =2*P(t_{84}>1.617) =0.1096[/tex]
We can use the following excel code to calculate it: "=2*(1-T.DIST(1.617;84;TRUE))"