a) The test statistic for the two independent samples is 0.7
b) The p-value for the test sample is 0.483 , here p-value is greater than significance level.Thus, there is no sufficient evidence to reject null hypothesis.
Given,
significance level, \alpha = 0.04
From population 1,
Mean, [tex]x_1=13.2[/tex]
variance, [tex]\sigma^2_1=39[/tex]
standard deviation, [tex]\sigma_1 =6.24[/tex]
sample size,[tex]n_1=62[/tex]
From population 2,
Mean, [tex]x_2=11.5[/tex]
variance, [tex]\sigma^2_2 = 29[/tex]
standard deviation, [tex]\sigma_2=4.47[/tex]
Test hypothesis,
[tex]H_0:(\mu_1-\mu_2)=1.6\\\\H_a:(\mu_1-\mu_2)\neq1.6[/tex]
a)
The test statistic can be determined by formula,
[tex]z=\frac{(x_1-x_2)-d}{\sqrt{\frac{S^2_1}{n^2_1}+\frac{S^2_2}{n_2}}}[/tex]
[tex]d=\mu_1-\mu_2=1.6[/tex]
[tex]z=\frac{(13.2-11.5)-1.6}{\sqrt{\frac{6.24^2}{62^2}+\frac{4.47^2}{51}}}\\\\z=\frac{0.1}{\sqrt{0.01+0.007}}\\\\z=\frac{0.1}{0.13}=0.7[/tex]
b)
P-value can be calculated by the z-score table
as z=0.7 then from z-value table
p=0.483
A p-value greater than 0.04 (> 0.04) indicates strong support for the null hypothesis. This means that the null hypothesis is retained and the alternative hypothesis is rejected. It is important to note that you cannot accept the null hypothesis; we can only reject it or fail to reject it.
To learn more about test statistic refer here
https://brainly.com/question/14128303
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