Sampling methods, inferential statistics and coverage error

1) What is the difference between probability sampling and simple random sampling?
A. There is no difference.
B. Simple random sampling is a type of probability sampling.
C. Probability sampling is a type of simple random sample.
D. In probability sampling each item has an identical chance of being chosen.

2) A survey was mailed to a total of 400 students; 100 were randomly selected from each of the freshman, sophomore, junior and senior classes last semester. What sampling method was used?
A. Cluster sample
B. Systematic sample
C. Stratified sample
D. Simple random sample

3) A sufficiently large coverage error will result in which of the following?
A. Non-response bias
B. Statistics about the actual population rather than the target population
C. Probability sampling
D. Inability to perform inferential statistics

4) Which of the following is not a characteristic of an ideal statistician?
A. Technically current (e.g. software)
B. Adapts answers to client desires
C. Communicates well (both written and oral)
D. Can deal with imperfect information

5) Which of the following statements is false?
A. A summary measure calculated from all items of interest is a parameter.
B. The main goal of descriptive statistics is to estimate characteristics of populations.
C. A summary measure calculated from some of the items of interest is a statistic.
D. Statistical inference is the process of making a prediction based on only a small piece of information.

6) Which of the following is an example of statistical inference?
A. Counting the number of patients who file malpractice suits after being discharged from hospitals in New York State.
B. Calculating the mean age of patients discharged from hospitals in New York State in 1997.
C. Calculating the mean number of fruit trees damaged by Mediterranean fruit flies in California last year.
D. Calculating the amount of fly spray needed for your orchard next season.