Question

1 point) For each problem, select the best response. (a) A simple random sample of size...

1 point) For each problem, select the best response.

(a) A simple random sample of size n is defined to be

A. a sample of size n chosen in such a way that every unit in the population has a known nonzero chance of being selected.
B. a sample of size n chosen in such a way that every unit in the population has the same chance of being selected.
C. a sample of size n chosen in such a way that every set of n units in the population has an equal chance to be the sample actually selected.
D. All of the above. They are essentially identical definitions.

(b) A small college has 500 male and 600 female undergraduates. A simple random sample of 50 of the male undergraduates is selected, and, separately, a simple random sample of 60 of the female undergraduates is selected. The two samples are combined to give an overall sample of 110 students. The overall sample is

A. a simple random sample.
B. a stratified random sample.
C. a systematic sample.
D. convenience sampling.
E. a multistage sample.

(c) In order to take a sample of 1200 people from a population, I first divide the population into men and women, and then take a simple random sample of 500 men and a separate simple random sample of 700 women. This is an example of a

A. randomized comparative experiment.
B. stratified random sample.
C. a simple random sample.
D. a multistage sample.
E. convenience sampling.

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Answer #1

a)

C. a sample of size n chosen in such a way that every set of n units in the population has an equal chance to be the sample actually selected.

b)

B. stratified random sample.
Stratified sampling refers to a type of sampling method. With stratified sampling, the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group.

c)

B. stratified random sample.
Stratified sampling refers to a type of sampling method. With stratified sampling, the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group.

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