The residential division of Prism's high-speed Internet service uses one advertising agency, while its commercial division uses another. Two analysts, Andy and Brad, are asked to test the effectiveness of the two agencies. Andy proposes an A/B test that compares the click-through rates per ad of the two agencies. Brad proposes a difference-in-difference test in which the budgets for both agencies are increased by 50%, and the percentage changes in the click-through rates are compared. What might be the sources of selection bias for the two proposals? Which is likely to be smaller?

Issues with "representatives"; Andy.

Explanation:

So, from the question we can see that; '' est the effectiveness of the two agencies. Andy proposes an A/B test that compares the click-through rates per ad of the two agencies. Brad proposes a difference-in-difference test in which the budgets for both agencies are increased by 50%, and the percentage changes in the click-through rates are compared."

Andy proposes an A/B test is based on randomized data and what A/B test does is to compare the click through rates of the two agencies.

Brad proposes a difference-in-difference test is based on data that are not treated randomly.

The proposal that is more likely to be biased is that of the proposal by Andy and this can be attributed to the issue known as the "representatives" that is to say to say that there are limited verification which will make Andy's proposal to be biased.

answer: tell me how

explanation:

hi : ) i found this so i hope this !

"we first find value of tax in dollars.

the difference between the two prices   is: 23. 54 - 22 = 1.54

therefore the sales tax in dollars is 1.54

the tax % will be   (amount of tax / original cost price ) × 100

(1.54 / 22) × 100  → (0.07) × 100 =   7

so the tax rate is 7%

we can double check the answer.

7 % of 22   → (7/100) × 22 → 0.07 × 22 = 1.54

22 + 1.54 = 23.54"