Ch 6 Sampling

Question 1

representative sample

Answer 1

accurately reflects the distribution of relevant variables in the target population

Should have all the same characteristics as the population

(considered a small reproduction of the population)

Question 2

population

Answer 2

Refers to all possible cases of what we are interested in studying

Should specify four things: Content, Units, Extent, Time

Question 3

sample

Answer 3

Consists of one or more elements selected from a population

Question 4

sampling frame

Answer 4

a listing of all the elements in a population

Question 5

to develop sampling frames for household-based surveys of populations that are large (like city or state), 2 listings should be considered …

Answer 5

telephone numbers and lists of addresses in a community (addressed based sampling)

Question 6

example of poor sampling frames

Answer 6

literary digest - pulled sample from car owners and telephone numbers to see who would win election, but most voters didn’t own cars or phones. their prediction was wrong of who won

Question 7

probability samples

Answer 7

samples in which each element in the population has a known chance of being selected into the sample

enables us to calculate sampling error

Question 8

Probability sampling includes what 4 types of sampling?

Answer 8

simple random sampling

systematic sampling

stratified sampling

area sampling

Question 9

sampling error

Answer 9

an estimate of the extent to which the values of the sample differ from those of the population from which it was drawn

Question 10

Simple random sampling (SRS)

Answer 10

each element in the population has an equal probability of inclusion in the sample

treats the target population as a unitary whole

it is often impractical because of cost

usually limited to small scale projects

it is the basic sampling procedure and the standard for other sampling procedures

Question 11

Systematic sampling

Answer 11

Involves taking every kth element listed in a sampling frame

Uses the table of random numbers to determine a random starting point in the sampling frame

Value of k is the sampling interval and is determined by dividing population size by desired sample size

We use this when we draw samples by hand rather than computer

Clerical efficiency

Can produce biased samples

Question 12

Stratified sampling

Answer 12

Divides the population into smaller subgroups, called strata, before drawing the sample and then draws separate random samples from each of the data

It reduces sampling error

Makes each subsample more homogeneous

Proportionate sampling

Disproportionate sampling

Question 13

Proportionate sampling

Answer 13

is where the size of the sample taken from each stratum is proportionate to the stratum’s presence in the population

Question 14

Disproportionate sampling

Answer 14

is when each element of a stratum has an equal chance of appearing in the sample of that stratum, but the elements in some strata have a better chance of appearing in the overall sample than the elements of other strata

Question 15

Area sampling

Answer 15

Also called cluster sampling OR multistage sampling

It’s a procedure in which we obtain the final units to include in the sample by first sampling among larger units, called clusters, that contain the smaller sampling units

Sampling from large to smaller units

Selected blocks within an area may contain different numbers of people

Estimation of sampling error

Question 16

a key issue in selecting a sample is that it ….

Answer 16

represent the population from which it was drawn

Question 17

what 5 things influence sample size?

Answer 17

research hypotheses - sufficient cases to study

precision - amount of sampling error you accept

population homogeneity - variability of sampled population

sampling fraction - number of elements in sample relative to the number of elements in population

sampling technique

Question 18

what formula to determine sample size?

Answer 18

r^n x 20 = sample size

r = number of values on each variable

n = number of variables

Question 19

NonProbability sampling includes what 5 types of sampling?

Answer 19

availability sampling

snowball sampling

quota sampling

purposive sampling

dimensional sampling

Question 20

nonprobability samples

Answer 20

the investigator does not know the probability of each population element’s inclusion in the sample

useful when goal of research is to see whether a relationship exists

useful in some qualitative research to understand social process

useful when its impossible to develop sampling frame

Question 21

limitations to non probability samples

Answer 21

make no real claim of representativeness

degree of sampling error remains unknown

statistical tests of significance

Question 22

availability sampling

Answer 22

also called convenience sampling OR accidental sampling

researchers take whichever elements are readily available

popular for research that is difficult or impossible to develop complete sampling frame

often used in experimental or quasi-experimental research

less expensive

impossible to develop exhaustive sampling frame

Question 23

snowball sampling

Answer 23

start with few cases of the type we want to study, which leads to more cases, and so on

depends on sampled cases being knowledgeable of other cases

used for sampling subcultures

useful in investigation of sensitive topics like that of child or drug abuse

allows for interactive sampling – people interact with each other

limitation: misses people who are isolated from such networks

Question 24

quota sampling

Answer 24

divides a population into various categories and then sets quotas on the number of elements to select from each category.

Nonprobability technique that depends on availability

Has declined in popularity

Research have quotas for common demographic characteristics like age, sex, race

Interviewers do the actual selection of respondents - shortcoming

Cheaper and faster than probability sampling

Question 25

Purposive sampling

Answer 25

Investigators use their judgement and prior knowledge to choose for the sample people who best serve the purposes of the study

Question 26

Dimensional sampling

Answer 26

Technique for selecting small samples in a way that enhances their representativeness

Specify all important dimensions or variables

Choose sample that includes at least one case that represents each possible combo of dimensions

Its faster and less expensive

Valuable in exploratory studies

Provides more detailed knowledge of each case

Some research uses both probability and nonprobability samples in one project

Suggestive rather than conclusive

Question 27

the key to selecting scientifically valid samples is…

Answer 27

to ensure their representativeness so we can make valid generalizations

Question 28

human services practitioners do not routinely engage in sampling procedures. true or false?

Answer 28

true