Answer:
[tex] SE= \sqrt{\frac{\sigma^2_1}{n_1}+\frac{\sigma^2_2}{n_2}}[/tex]
And for this case if we have the same sample size we got the minimum value when we have the higher value fo n for each one and for this case would be the answer:
b. 120
Step-by-step explanation:
For this case we have the following info given:
[tex] n_1 = n_2 = 100[/tex]
[tex]\mu_1 = 85.6[/tex]
[tex]\mu_2 = 82.1[/tex]
[tex] \sigma_1 =12.4[/tex]
[tex]\sigma_2 = 8.9[/tex]
We assume that the variable of interest is the linear combination of the two means and for this case the standard error would be given by:
[tex] SE= \sqrt{\frac{\sigma^2_1}{n_1}+\frac{\sigma^2_2}{n_2}}[/tex]
And for this case if we have the same sample size we got the minimum value when we have the higher value fo n for each one and for this case would be the answer:
b. 120