Sampling

Question 1

Population

Answer 1

Entire Group of Interest

Question 2

Sample

Answer 2

The subset of the population that is chosen for the study

Question 3

Census

Answer 3

When every member of a population is included in the study

Question 4

Sampling

Answer 4

The process by which the researcher chooses a sample from a population

Question 5

Goals of Sampling?

Answer 5

External validity, economic sample, representation of the population

Question 6

Representative Sample (Unbiased Sample)

Answer 6

All members of the population have an equal chance of being included in the sample

Question 7

Sampling Error

Answer 7

The extent to which the sample is not representative

Question 8

Unrepresentative Sample (Biased Sample)

Answer 8

(also known as nonprobability + nonrandom)Sample in which some members of the population are left out (some members may be over/underrepresented).

Question 9

What are the 2 sampling techniques?

Answer 9

Probability + Nonprobability

Question 10

What are the 4 types of probability sampling?

Answer 10

Simple random sampling, systematic sampling, cluster sampling, stratified random sampling

Question 11

What are the 4 types of nonprobability sampling?

Answer 11

Convience sampling, quota sampling, purposive sampling, snowball sampling

Question 12

Probablity Sampling

Answer 12

(also known as random) Results in an unbiased or representative sample - Each member of the pop. has an equal chance of being included

Question 13

Simple random sampling

Answer 13

Choose random set of people from entire pop. to be in your sample (EX: use a random number table or random # generator)

Question 14

Systematic Sampling

Answer 14

Choosing “ever so many” individuals for the sample (do not need a sampling frame) (EX: choose every 4th person that comes into the ER)

Question 15

Do you need a sampling for simple random sampling?

Answer 15

Yes - The name and contact info for everyone in your population

Question 16

Cluster Sampling

Answer 16

Clusters of participants w/n the population are selected at random. Collect data from every ind. in each cluster

Question 17

Multistage Sampling

Answer 17

Clusters of participants w/n a population are selected at random, then you collect data from a random sample w/n each cluster

Question 18

Stratified random sampling

Answer 18

Researcher identifies a particular sociodemographic category (strata). Choose randomly w/n each category

Question 19

Proportionate sampling method

Answer 19

Sampling is chosen in proportion to its representation in the population

Question 20

*Additional Information about Cluster/Multistage

Answer 20

Cluster are not selected w/proportions in mind. They often use naturally divided groups (school districts, etc.)

Question 21

*Additional Information about Stratified

Answer 21

Final sample sizes of each strata are proportional to those in the population. Divide the population based on shared characteristics (occupation, age, race, etc.)

Question 22

Convenience Sampling

Answer 22

Sample consisting of people who are easy to contact and readily available

Question 23

Quota Sampling

Answer 23

Researcher ensures a certain number of percentage of people from a particular group(s) are included in the sample

Question 24

Purposive Sampling

Answer 24

Only recruiting certain kinds of people in your sample
(EX: study on barriers to cancer screening)

Question 25

Snowball Sampling

Answer 25

Participants are asked to recommend a few acquaintances for the study
(EX: recruiting parents w/toddlers)

Question 26

Self-Selection

Answer 26

When a sample contains only people who volunteered to participate. Automatic in nonprobability samples, but can happen w/ probability samples. A sample containing too many of the most unusual people

Question 27

Misgeneralization

Answer 27

Attempting to generalize results based on unrepresentative people

Question 28

Nonprobability - “WEIRD Samples”

Answer 28

Western, Educated, Industrialized, Rich, Democratic

Question 29

*Notes on sample size

Answer 29

Having a larger sample does not always make our sample more representative. For external validity of a sample, it is HOW and NOT HOW MANY. Sample size is a statistical validity issue, not an external validity issue