Chapter 8

Question 1

Accidental Sampling

Answer 1

we simply reach out and take the cases that are at hand, continuing the process until the sample reaches a designated size.

Question 2

Biases

Answer 2

systematic deviations of sample means from true population values, introduced in such samples.

Question 3

Census

Answer 3

a count of all the elements in a population and/or a determination of the distributions of their characteristics, based on information obtained for each of the elements.

Question 4

Confidence Level

Answer 4

the probability that the value of a parameter falls within a specified range of values.

Question 5

Domain Sampling

Answer 5

identical to the logic of sampling in general. “The person’s performance on the sample of items contained in a measure is used as a basis for estimating the desired construct, his or her hypothetical performance on the entire domain.”

Question 6

Nonprobability Sampling

Answer 6

There is no way to estimate the probability each element has of being included in the sample and no assurance that every element has some chance of being included.

Question 7

Particularistic Research Goals

Answer 7

external validity amounts to the ability to generalize the research results themselves from the studied sample to the target population, and sampling is a crucial step enhancing that ability.

Question 8

Population

Answer 8

the aggregate of all of the cases that conform to some designated set of specifications. Thus, by the specifications “people” and “residing in the United States”, we define a population of all the people who reside in the United States.

Question 9

Population element

Answer 9

a single member of a population is referred to as a population element.

Question 10

Probability Sampling

Answer 10

one can specify for each element of the population the probability that it will be include in the sample.

Question 11

Purposive Sampling

Answer 11

Basic assumption behind purposive sampling is that with good judgment and an appropriate strategy, we can handpick the cases to be included and thus develop samples that are satisfactory in relation to our needs.

Question 12

Quota Sampling

Answer 12

adds insurance of the second type referred to earlier – provisions to guarantee the inclusion of diverse elements of the population and to make sure that they are taken account of in the proportions in which they occur in the population.

Question 13

Representative Sampling Plan

Answer 13

a sampling plan that carries such insurance is referred to as a representative sampling plan. What a representative sampling plan can do is to ensure that the odds are great enough so that the selected sample is, for the purposes at hand, sufficiently representative of the population to justify our running the risk of taking it as representative.

Question 14

Sample

Answer 14

when we select some of the elements with the intention of finding out something about the population from which they are taken, we refer to that group of elements as a sample.

Question 15

Sampling Distribution

Answer 15

we take every combination of the desired number of cases and compute a mean for each combination. What results is a distribution of sample means.

Question 16

Sampling Plans

Answer 16

“we could devise a number of sampling plans that would carry the insurance that our estimates do not differ from the corresponding true population figures by, say, more than 5% on more than, say, 10% of these occasions; the estimates will be correct within 5 percentage points (the margin of error) 90% of the time (the probability or confidence level).

Question 17

Simple Random Sampling

Answer 17

the basic probability sampling design, it is incorporated in all more complex probability sampling designs. A simple random sample is selected by a process that not only gives each element in the population an equal chance of being included in the sample, but also makes the selection of every possible combination of the desired number of cases equally likely.

Question 18

Snowball Sampling

Answer 18

a multistage sampling procedure by which a small initial sample “snowballs” into a sample large enough to meet the requirements of research design and data analysis.

Question 19

Stratum

Answer 19

defined by one or more specifications that divide a population into mutually exclusive segments. For example, a given population could be subdivided into strata consisting of males under 21 years of age, females under 21 years of age, etc.

Question 20

Universalistic Research Goals

Answer 20

consistency or inconsistency of findings with the theoretically based hypotheses in the sample is the key outcome, for inconsistency implies that the theory is inadequate and requires revision.