The next three questions concern this situation: You're working on a story about complaints that minority drivers are being targeted for traffic tickets by the police in your town. License records tell you that 20% of the drivers in your town are minorities. You examine a properly-drawn random sample of 560 tickets, out of the 8,322 tickets issued last year, and find that 168 of the tickets in your sample were given to minority drivers.

First question: What proportion of the tickets in your sample were given to minority drivers?

100%

84%

30%

8.4%

0.3%

Continuing with the scenario above, knowing that minority drivers should get about 20% of the tickets if there was no bias, calculate the relative risk of minority drivers getting tickets compared to what they should get.

The relative risk for minority drivers is 0.67

The relative risk for minority drivers is 1.0

The relative risk for minority drivers is 1.5

The relative risk for minority drivers is 2.0

The relative risk for minority drivers is 30

Continuing with the scenario above, the police chief says that he will hire someone to tally all 8,322 tickets to prove you are wrong and that there is no bias is how tickets are issued. You want to be at least 95% confident that the error margin around your sample of 560 tickets is such that even the low end is well above 20%. So you think of it as being like a survey of 560 randomly selected drivers. Use the formula for sampling error margin to calculate the error margin for this sample.

25.8% to 34.2%

23.7% to 36.2%

26.1% to 33.7%

22.3% to 33.9%

27.8% to 31.5%

Exactly 30%, the same proportion as in the sample.