Chapter 7: The Logic of Sampling

Question 1

Any technique in which samples are selected in some way not suggested by probability theory.

Answer 1

Nonprobability Sampling

Question 2

What are the four types of nonprobability sampling?

Answer 2

(1) Reliance on available subjects, (2) purposive of judgemental sampling, (3) snowball sample, and (4) quota sampling

Question 3

Stopping people on the street is an example of

Answer 3

Reliance on available subjects (aka haphazard or convenience sampling

Question 4

A type of nonprobability sampling in which the units to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative.

Answer 4

Purposive Sampling or Judgemental Sampling

Question 5

A nonprobability-sampling method, often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing

Answer 5

Snowball Sampling (aka Chain Referral)

Question 6

A type of nonprobability sampling in which units are selected into a 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

Answer 6

Quota Sampling

Question 7

Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.

Answer 7

Informant

Question 8

People who provide information about themselves to social researchers

Answer 8

Respondents

Question 9

The general term for samples selected in accordance with probability theory, typically involving some random-selection mechanism.

Answer 9

Probability Sampling

Question 10

What are some specific types of probability sampling?

Answer 10

EPSEM, PPS, Simple Random Sampling, and Systematic Sampling

Question 11

What is the advantage of probability sampling?

Answer 11

It guarentees the sample we observed is representative of the whole population being studied

Question 12

What is the fundamental idea behind probability sampling?

Answer 12

In order to provide useful descriptions of the total population, a sample of individuals from a population must contain essentially the same variations that exist in the population.

Question 13

Those selected are not typical pr representative of the larger population they’ve been chosen from

Answer 13

Sampling Bias

Question 14

That quality of a sample having the same distribution of characrestics as the population from which it was selected. By implication, descriptions and explanations derived from an analysis of the sample may be assumed to represent similar ones in the population.

Answer 14

Representativeness

Question 15

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

Answer 15

EPSEM (Equal Probability of Selection Method)

Question 16

What are two major advantages of probability sampling?

Answer 16

Lack of bias and accuracy

Question 17

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

Answer 17

Element

Question 18

The theoretically specified aggregation of the elements in a study

Answer 18

Population

Question 19

The aggregation of elements from which a sample is actually selected

Answer 19

Study Population

Question 20

A sampling method in whuchg each element has an equal chance of selectuib independent of any other event in the selection process. (Ex. flipping a coin)

Answer 20

Random Selection

Question 21

That elemenet or set of elements considered for selection in some stage of sampling

Answer 21

Sampling Unit

Question 22

The summary description of a given variable in a population

Answer 22

Parameter

Question 23

What are two reasons for using random selection?

Answer 23

(1) Serves as a check on conscious or subconscious bias & (2) offers access to the body of probability theory

Question 24

A branch of mathematics that provides the tolls researchers need (1) to devise sampling techniques that produce representative samples and (2) to statistically analyze the results of their sampling.

Answer 24

Probability Theory

Question 25

The summary description of a variable in a sample, used to estimate a population parameter.

Answer 25

Statistic

Question 26

The degree of error to be expected in probability sampling. Formula contains three factors: The parameter, the sample size, and the standard error

Answer 26

Sampling error

Question 27

Sampling Error Formula

Answer 27

s= √ (PxQ/n)

Question 28

Population parameters for the binomial in sampling error formula

Answer 28

P & Q

Question 29

What percent of samples must fall within plus or minus two standard errors of the true value in probability theory?

Answer 29

95%

Question 30

What percent of samples must fall within plus or minus three standard errors of the true value in probability theory?

Answer 30

99.9%

Question 31

The estimated probability that a population parameter lies within a given confidence interval.

Answer 31

Confidenece Level

Question 32

The range of values within which a population parameter is estimated to lie.

Answer 32

Confidence Interval

Question 33

That list or quasi list of units composing a population from which a sample is selected.

Answer 33

Sampling Frame

Question 34

Findings based on a sample can be taken as representing only…

Answer 34

the aggregation of elements that compose the sampling frame

Question 35

Researchers must research and correct if possible

Answer 35

omissions to the sampling frame

Question 36

To be geneeralized even to the population composing the sampling frame…

Answer 36

all elements myst have eqeual representation in the frame

Question 37

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.

Answer 37

Simple Random Sampling

Question 38

A type of probability sampling in which every kth unit in a list is selected in the sample–for example, every 25th student in the college directory

Answer 38

Systematic Sampling

Question 39

The dtandard distance (k) between elements selected from a population for a sample ( = Population size/Sample size)

Answer 39

Sampling Interval

Question 40

The proportion of elements in the population that are selected to be in a sample ( = Sample size/Population size)

Answer 40

Sampling Ratio

Question 41

The grouping of the units composing a population into homogeneous groups (or strata) before sampling. This procedure, which may be used in conjunction with the simple random, systematic, or cluster sampling, improves the representativeness of a sample.

Answer 41

Stratification

Question 42

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

Answer 42

Cluster Sampling

Question 43

Sampling error is reduced by what two factors?

Answer 43

(1) An incease in the sample size and (2) increased homogeneity of the elements being sampled.

Question 44

This refers to a type of multistage cluster 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 tonbe subsampled

Answer 44

PPS (Probability Proportionate to Size)

Question 45

Assigning different weights to cases that were selected into a sample with different probabilities of selection. In the simplest scenario, each case is given weight equal to the inverse of its probability of selection. When all cases have the same chance of selection, this is not necessary.

Answer 45

Weighting