A test was made of H0: μ1 = μ2 versus H1: μ1 < μ2. The sample means were and the sample standard deviations were and and the sample sizes were and Is H0 rejected at the 0.05 level? (Hint: First compute the value of the test statistic.)

Respuesta :

Answer:

Step-by-step explanation:

Hello!

Hypotheses:

H₀: μ₁ = μ₂

H₁: μ₁ < μ₂  

α: 0.05

Using the following sample information:

Sample 1

n₁= 15

X[bar]₁= 10

S₁= 4

Sample 2

n₂= 27

X[bar]₂= 8

S₂= 7

This is an example of a t-test for independent samples, assuming both unknown populations variances are equal the statistic is:

[tex]t= \frac{(X[bar]_1-X[bar]_2)-(Mu_1-Mu_2)}{Sa*\sqrt{\frac{1}{n_1} +\frac{1}{n_2} } } ~~t_{n_1+n_2-2}[/tex]

[tex]Sa= \sqrt{\frac{(n_1-1)S^2_1+(n_2-1)S^2_2}{n_1+n_2-2} } = \sqrt{\frac{14*16+26*49}{15+27-2} }= \sqrt{\frac{1498}{40} } = 6.119= 6.12[/tex]

[tex]t= \frac{(10-8)-0}{6.12*\sqrt{\frac{1}{15} +\frac{1}{27} } }= 1.01[/tex]

The p-value of this test is 0.1593

To decide using the p-value approach you have to use the following rule:

If p-value ≤ α, reject the null hypothesis.

If p-value > α, do not reject the null hypothesis.

The calculated p-value is greater than the significance level, the decision is to not reject the null hypothesis.

Using a 5% significance level you can conclude that the hypothesis test is not significant and the population means of populations 1 and 2 are equal.

I hope this helps!

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