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!