Ch 7

Question 1

Generalizability

Answer 1

does the sample represent the population

Question 2

External Validity is especially important in what type of claims?

Answer 2

frequency claims

Question 3

Population

Answer 3

entire set of people or things/products of interest

Question 4

Sample:

Answer 4

smaller set taken from the population to represent it

Question 5

Census

Answer 5

sampling every member of the population

Question 6

Population of interest

Answer 6

population to which we want our research findings to generalize

Question 7

If a sample has good external validity, we can say

Answer 7

the sample “generalizes to” or “is representative of” the population

Question 8

Biased sample (unrepresentative sample)

Answer 8

not all members of a population have an equal chance of being included

Question 9

Unbiased sample (representative sample):

Answer 9

all members of a population have an equal chance of being included

Question 10

Ways to get a biased sample:

Answer 10

• convenience sampling

- self-selection

Question 11

Convenience sampling

Answer 11

sampling only those easy to contact

Question 12

Self-selection

Answer 12

sampling only those who volunteer

Question 13

Probability sampling (random sampling/ random selection)

Answer 13

all members of a population have an equal chance of being included

Question 14

Nonprobability sampling

Answer 14

involves nonrandom, biased sampling

Question 15

Simple random sampling

Answer 15

names in a pool and randomly selecting a predetermined number of names

Question 16

Cons of simple random sampling

Answer 16

• difficult
• time consuming
• Impossible if you can’t enumerate population of interest

Question 17

types of probability sampling

Answer 17

• simple random sampling
• Cluster sampling
• Multistage sampling
• Stratified random sampling
• Oversampling
• Systematic sampling

Question 18

Cluster sampling

Answer 18

randomly choosing groups/ clusters within a population and using all people in the chosen groups

Question 19

Multistage sampling:

Answer 19

2 random sampling stages:

• 1st randomly choosing groups/ clusters
• then choosing a random sample within each chosen group

Question 20

Stratified random sampling

Answer 20

selecting demographic categories (strata) then randomly choose people within each category, proportionate to their % in the population

Question 21

Oversampling

Answer 21

• selecting demographic categories (strata) then randomly choose people within each category, then over representing one or more groups
• have to adjust statistics on back end

Question 22

Weighting

Answer 22

statistical technique to control for bias so that subgroups are properly represented according to their weight in the actual population

Question 23

Systematic sampling

Answer 23

using a computer or random # table, choosing 2 random numbers (4 and 7 for ex) and then choosing the 4th person in the room and every 7th person until the desired sample number is reached

Question 24

Random sampling (probability sampling)

Answer 24

creating a sample in a way that enhances external validity, so that each member of the population has an equal chance of being in the sample

Question 25

Random assignment

Answer 25

used ONLY in experiments, to assign participants to groups at random (like treatment and comparison groups) increases internal validity

Question 26

Types of non-probability sampling:

Answer 26

- Convenience sampling - Purposive sampling - Snowball sampling - Quota sampling

Question 27

Convenience Sampling

Answer 27

samples that are easy to access | - common in behavioral research

Question 28

Purposive sampling

Answer 28

using only the type of people the researchers want to study, in a non-random way

Question 29

Snowball sampling

Answer 29

variation of purposive sampling in which participants are asked to recommend other participants

Question 30

Quota Sampling

Answer 30

similar to stratified random sampling- | - identifies subsets of interest, then set a target # for each subset. Sample non-randomly until quotas are filled.

Question 31

when a non-probability sample is used, ask:

Answer 31

Are the characteristics that make the sample biased relevant to what's being measured?

Question 32

if a sample isn't externally valid, it...

Answer 32

has unknown external validity

Question 33

ways of saying a sample is random or not

Answer 33

- Unbiased sample/ biased sample - Probability sample/ nonprobability sample - Random sample/ nonrandom sample - Representative sample/ unrepresentative sample

Question 34

are large samples more representative than smaller samples?

Answer 34

- Large samples are not more representative than smaller samples (If the larger sample is not more representative than a smaller sample would be) - A researcher chooses a sample size for a poll in order to optimize the margin of error for the estimate (the degree of sampling error)