Chapter 6 Sampling

Question 1

Error

Answer 1

Any difference between reported results and true scores.

Question 2

Census

Answer 2

All members of a population.

Question 3

Sample

Answer 3

A selection of members from a population.

Question 4

Random Error

Answer 4

Refers to mistakes that are equally likely to occur.

Question 5

Bias

Answer 5

A form of systematic error.

Question 6

Nonprobability Sampling

Answer 6

Any technique is which samples are selected in some fashion not suggested by probability theory. Examples are purposive (judgemental), snowball, and quota sampling, as well as reliance on available subjects.

Question 7

Purposive Sampling

Answer 7

A type of nonprobability sampling in which you select the units to be observed on the basis of your own judgement about which ones will be the most useful or representative. Another name for this is judgemental sampling.

Question 8

Snowball Sampling

Answer 8

A nonprobability sampling method often used in field research in which each person interviewed may be asked to suggest additional people for interviewing.

Question 9

Quota Sampling

Answer 9

A type of nonprobability sampling in which units are selected into the sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied.

Question 10

Informant

Answer 10

Someone well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows. If you were planning participation observation among the members of a religious sect, you would do well to make friends with someone who already knows about them - possibly a member of the sect- who could give you some background information about them. Not to be confused with a respondent.

Question 11

Saturation

Answer 11

A sampling principle used in qualitative studies that encourage adding cases until new insights are unlikely.

Question 12

Probability Sampling

Answer 12

The general term for samples selected in accord with probability theory, typically involving random selection mechanisms. Specific types of probability sampling include EPSEM, PPS, simple random sampling.

Question 13

Sampling Bias

Answer 13

Systematic error derived from using nonprobability samples that produces unrepresentative results.

Question 14

Representativeness

Answer 14

That quality of a sample of having the same distribution of characteristics as the population from which it was selected. By implication, descriptions and explanations derived from an analysis of the sample may be assumed,ed to represent similar ones in the population. Representativeness is enhanced by probability sampling and provides for generalizability and the use of inferential statistics.

Question 15

EPSEM (Equal Probability of Selection Method)

Answer 15

A sample design in which each member of a population has the same chance of being selected into the sample.

Question 16

Sampling Error

Answer 16

The discrepancy between the characteristics of a probability sample and the characteristics of the population. The more representative the sample, the smaller the sampling error, and the more accurate the sample-derived estimates of population characteristics will be.

Question 17

Element

Answer 17

The unit of which a population is composed and which is selected in a sample. Distinguished from units of analysis, which are used in data analysis.

Question 18

Population

Answer 18

The theoretically specified aggregation of the elements in a study.

Question 19

Study Population

Answer 19

The aggregation of elements from which a sample is actually selected.

Question 20

Random Selection

Answer 20

A sampling method in which each element has an equal chance of selection independent of any other event in the selection process.

Question 21

Sampling Unit

Answer 21

The element or set of elements considered for selection in some stage of sampling.

Question 22

Sampling Frame

Answer 22

The list or quasi-list of units that make up a population from which a sample is selected. If the sample is to be representative of a population, it is essential that the sampling frame include all (or nearly all) members of the population.

Question 23

Simple Random Sampling

Answer 23

A type of probability sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample. Although probability theory and the calculations it provides assume this basic sampling method, it’s seldom used, for practical reasons. An equivalent alternative is the systematic sample (with a random start).

Question 24

Systematic Sampling

Answer 24

A type of probability sampling in which every 4th unit in a list is selected for inclusion in the sample - for example, every 25th student in the university directory of students. You compute k by dividing the size of the population by the desired sample size; k is called the sample interval. Within certain constraints, systematic sampling is a functional equivalent of simple random sampling and usually easier to do. Typically, the first unit is selected at random.

Question 25

Sampling Interval

Answer 25

The standard distance (k) between elements selected from a population for a sample.

Question 26

Sampling Ratio

Answer 26

The proportion of elements in the population that are selected to be in the sample.

Question 27

Stratification

Answer 27

The grouping of the units making up a population into homogeneous groups (or strata) before sampling. This procedure, which may be used in conjunction with simple, random, systematic or cluster sampling improves the representativeness of a sample, at least with regard to the variables used for stratification.

Question 28

Cluster Sampling

Answer 28

A multistage sampling approach in which natural groups (clusters) are sampled initially, with the members of each selected group being subsampled afterward. For example, you might select a sample of Canadian universities from a directory, get lists of the students at all the selected schools, and then draw samples of students from each.

Question 29

PPS (Probability Proportionate to Size)

Answer 29

A type of multistage closer sample in which clusters are selected, not with equal probabilities (see EPSEM), but with probabilities proportionate to their sizes - as measured by the number of units to be subsampled.

Question 30

Weighting

Answer 30

A procedure used in connection with sampling whereby units selected with unequal probabilities are assigned weights in such a manner as to make the sample representative of the population from which it was selected. When all cases have the same chance of selection, no weighting is necessary.