Sampling

Question 1

What type of claim is external validity extremely important for?

Answer 1

Frequency claims

Question 2

What does external validity concern?

Answer 2

Both samples and settings

Question 3

External Validity

Answer 3

Whether the results of a study can be generalized to some larger population of interest

Question 4

Sample

Answer 4

The group of people, animals, or cases used in a study; subset of population of interest.

Question 5

Population

Answer 5

The entire set of people or products in which you are interested in.

Question 6

Census

Answer 6

A set of observations that contains all members of the population of interest.

Question 7

Biased (unrepresentative) Sample

Answer 7

A sample in which some members of the population have a higher probability of being chosen, and therefore the results cannot generalize to the population of interest.

Question 8

Population of Interest

Answer 8

The population researchers want to generalize too.

Question 9

Unbiased (representative) Sample

Answer 9

A sample in which all members of the population of interest are equally likely to be included, and therefore the results can be generalized to the population of interest.

Question 10

What do unbiased samples let us do?

Answer 10

Make inferences about the population of interest

Question 11

What are the biased sampling methods?

Answer 11

1. Convenience
2. Purposive
3. Snowball
4. Self Selected

Question 12

Convenience Sampling

Answer 12

Choosing a sample based on people who are easiest to access and readily available.
- biased

Question 13

Self Selection

Answer 13

A form of sampling bias that occurs when a sample contains only people who volunteer to participate.

Question 14

Snowball

Answer 14

A variation of purposive sampling, participants are asked to recommend acquaintances for the study.

Question 15

Why is snowball sampling not representative?

Answer 15

People are recruited by networking, not randomly.

Question 16

Purposive

Answer 16

Only certain kinds of people are included in a sample.

Question 17

What is an example of purposive sampling?

Answer 17

Researchers wanting to study the effectiveness of stopping smoking will only choose smokers by posting flyers at the local tobacco store.

• key point is the posting of flyers in a specific location

Question 18

What are 6 examples of representative sampling?

Answer 18

1. Simple random sampling
2. Systematic sampling
3. Cluster sampling
4. Multistage cluster sampling
5. Stratified random sampling
6. Oversampling

Question 19

Simple Random Sampling

Answer 19

The sample is chosen completely at random from the population of interest.

Question 20

What is the most basic form of probability sampling?

Answer 20

Simple random sampling

Question 21

What is an example of simple random sampling?

Answer 21

Bingo spinner with names on each ball
- Names pulled are a part of the sample

Question 22

Systematic Sampling

Answer 22

The researcher uses a randomly chosen number N and counts off every Nth member of a population to achieve a sample.

Question 23

What is an example of systematic sampling?

Answer 23

Choose every 7th person off of a list

Question 24

What are two cons about simple random sampling and systematic sampling?

Answer 24

Can be difficult and time consuming

Question 25

Cluster Sampling

Answer 25

Clusters of participants within the population of interest are selected at random, followed by data collection from all individuals in each cluster.

Question 26

What is an example of cluster sampling?

Answer 26

Sample Illinois high school students; make list of all public high schools, randomly select 100 of them and include all students from each of those 100 high schools.

Question 27

Multistage Sampling

Answer 27

A probability sampling technique involving two stages: a random sample of clusters followed by a random sample of people within the selected clusters.

Question 28

What is an example of multistage sampling?

Answer 28

Sample Illinois high school students; make list of all public high schools, randomly select 100 of them and then randomly select a sample of students from each of these schools.

Question 29

Stratified Random Sampling

Answer 29

The researcher identifies specific demographic categories, and then randomly selects individuals within each category.

Question 30

What is an example of stratified random sampling?

Answer 30

Want to make sure sample contains Canadians and South Asian Canadians: Identify south Asian Canadians and Canadians; members from each category selected at random.

Question 31

How is stratified random sampling different from cluster sampling?

Answer 31

The categories in stratified are meaningful while clusters are random sets.

Question 32

What do the final samples of categories in stratified random sampling reflect?

Answer 32

Their proportion within the population

Question 33

What do clusters of cluster sampling reflect?

Answer 33

Simple clusters - proportions are not kept in mind

Question 34

Oversampling

Answer 34

A variation of stratified random sampling where a researcher intentionally over represents one or more groups.

Question 35

Non probability Sampling

Answer 35

Nonrandom sampling that results in a biased sample.

Question 36

Is the sample size or random selection more important for external validity?

Answer 36

Random sampling is more important

Question 37

Statistical Validity

Answer 37

The accuracy of conclusions about relationships or differences. - how accurate statistics are

Question 38

What 2 things affect statistical validity?

Answer 38

- Sampling size - Representativeness

Question 39

What happens to the statistical validity when the sample size is too small?

Answer 39

Increased chance for type 2 errors (false negative)

Question 40

What happens to the statistical validity when the sample is poorly chosen?

Answer 40

Increases the chance for type 1 errors (false positive).