Match these examples with the type of bias that causes data distortion.

1. Halfway through the study, 3 people in the sample dropped out of the study, so we don't have numbers for them in the final observations.

2. We conducted a phone survey calling 1000 people. 795 people hung up on us when we were making the calls.

3. Survey:
Question 1:How much money do you spend on toll roads in our city in a month?

Question 2: Do you feel like the toll roads in our city cost too much?


4. Survey question: Do you support spending tax money on road improvements we really don't need?

5. After questioning a sample of size 100 from the residents of this small town, we believe that 45.87% of the population of the town will support the building of a new city park.

6. We want to determine the average height of Senior girls in the school, so we asked a sample of female students to tell us how tall they are.

7. Our study has determined that an increase in workplace injuries are due to employees being given a raise in hourly pay.

8. A local factory reports that their pollution control efforts are reducing their coal emissions by 15% over last year.


A. Correlation and Causality
B. Self-Interest Study
C. Precise numbers
D. Reported Results
E. Missing Data
F. Order of Questions
G. Nonresponse
H. Loaded Questions