A sample of 41 observations is selected from one population with a population standard deviation of 3.4. The sample mean is 100.0. A sample of 45 observations is selected from a second population with a population standard deviation of 5.6. The sample mean is 98.4. Conduct the following test of hypothesis using the 0.05 significance level. H0 : μ1 = μ2 H1 : μ1 ≠ μ2

a. One or two tail?

b. State the decision rule. The decision rule is to reject H0 if z is (Outside, Inside) the interval (____,____).

c. Compute value of Test statistic.

d. Reject or Do not reject?

e. what is the p value?

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))"

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