Samples and Populations

Question 1

Define populations

Answer 1

The entire collection of people that we’re interested in studying

Question 2

Define samples

Answer 2

A selection of individuals from the larger population that we’re interested in studying

Question 3

What are the 4 reasons why we sample instead of studying the population directly?

Answer 3

1) Save time (It will take forever to collect data from the population, too many people)

2) Save money (Collecting data from the population is expensive, production cost, payment to participants)

3) Easy access (Accessing the population is difficult and impossible)

4) Results from a sample is generally sufficient (Pattern of results doesn’t change much even if we have data from everyone)

Question 4

How do we sample? List 7 ways

Answer 4

1) Random sampling

2) Systematic sampling

3) Stratified proportional sampling

4) Stratified disproportional sampling

5) Cluster sampling

6) Opportunity sampling

7) Snowball sampling

Question 5

What sampling is when each member of the population has an equal chance of being selected (usually quasi-random)?

Answer 5

Random sampling

Question 6

What is Random Sampling?

Answer 6

When each member of the population has an equal chance of being selected (usually quasi-random)

Question 7

What sampling draws from the population at fixed intervals and is problematic in populations with a periodic function?

Answer 7

Systematic Sampling

Question 8

How do you conduct Random Sampling?

Answer 8

Usually assign a person in the population to a number and use a random number table to select a sample

Question 9

What is Systematic Sampling?

Answer 9

Sampling that draws from the population at fixed intervals and is problematic in populations with a periodic function

Question 10

How do you conduct Systematic Sampling?

Answer 10

You’d select members of the population at a regular interval

e.g. Selecting every 15th person on a list of the population

Question 11

What are the 2 types of Stratified Sampling?

Answer 11

1) Proportional

2) Disproportional

Question 12

What is Proportional Stratified Sampling?

Answer 12

When specified groups appear in numbers proportional to their size in the population

e.g. If the population was 60% female and 40% male, the sample would also be 60% female and 40% male to represent the population

Question 13

What sampling involves specified groups appearing in numbers proportional to their size in the population?

Answer 13

Proportional Stratified Sampling

Question 14

How do you conduct Proportional Stratified Sampling?

Answer 14

e.g. If the population was 60% female and 40% male, the sample would also be 60% female and 40% male to represent the population
(you would take 120 females and 80 males in a sample size of 200)

Question 15

What is Disproportional Stratified Sampling?

Answer 15

When specified groups which are not equally represented in the population, are selected in equal proportions

e.g. If the population was 60% female and 40% male, the sample would instead have a proportion of 50% female and 50% male

Question 16

What sampling involves specified groups which are not equally represented in the population, being selected in equal proportions?

Answer 16

Disproportional Stratified Sampling

Question 17

How do we conduct Disproportional Stratified Sampling?

Answer 17

e.g. If the population was 60% female and 40% male, the sample would instead have a proportion of 50% female and 50% male
(you would take 100 females and 100 males in a sample size of 200)

Question 18

What is Cluster Sampling?

Answer 18

When a researcher samples an entire group or
cluster from the population of interest

Question 19

What is one precaution of Cluster Sampling?

Answer 19

We must be careful to not generalise a whole population from a cluster

Question 20

What sampling involves a researcher sampling an entire group or cluster from the population of interest?

Answer 20

Cluster Sampling

Question 21

How do we conduct Cluster Sampling?

Answer 21

e.g. Divide a population info clusters (districts, schools, neighbourhoods) and then randomly select some of these clusters as samples

Question 22

What is Opportunity/Convenience Sampling?

Answer 22

When we use people who are easily available as our sample

Question 23

What sampling involves using people who are easily available as a sample?

Answer 23

Opportunity/Convenience Sampling

Question 24

How do we conduct Opportunity/Convenience Sampling?

Answer 24

e.g. Asking members of the population of interest if they would like to participate in the study

Question 25

What is one problem with Opportunity/Convenience Sampling?

Answer 25

This can lead to a biased sample

Question 26

What is Snowball Sampling?

Answer 26

When you recruit a small number of participants and then use those initial contacts to recruit further participants (recruit using connections)

Question 27

Which sampling involves recruiting a small number of participants and then using those initial contacts to recruit further participants?

Answer 27

Snowball Sampling

Question 28

What is one limitation and benefit of Snowball Sampling?

Answer 28

Con = Biases the sample Pro = Useful if you want to recruit very specific populations

Question 29

How do you conduct Snowball Sampling?

Answer 29

Recruit participants through existing participants e.g. We ask existing participants if they could recommend and nominate additional potential participants

Question 30

Define External validity

Answer 30

The ability to generalise our results outside of the lab

Question 31

Define Population validity

Answer 31

Is our sample representative of the population?

Question 32

Define Ecological validity

Answer 32

Does the behaviour measured reflect naturally, occurring behaviour? Do our results apply to people outside of laboratory settings/ in real-world settings?

Question 33

What are the 3 factors that help you decide on a sample size?

Answer 33

1) Design (subjects design, number of IVs or IV levels) 2) Response rate of the potential participants 3) Heterogeneity of population

Question 33

What are the 3 factors that help you decide on a sample size?

Answer 33

1) Design (subjects design, number of IVs or IV levels) 2) Response rate of the potential participants 3) Heterogeneity of population

Question 34

What sampling is this based on? You want to get shoppers' opinions on a set of logos for a new product, you ask every 100th person who passes you on a central shopping street on a Saturday morning.

Answer 34

Systematic sampling

Question 35

What sampling is this based on? You want to ask psychiatrists about the limitations of current services offered to people with psychosis. You contact a few psychiatrists, and ask them if they know other people who might take part

Answer 35

Snowball sampling

Question 36

What sampling is this based on? You want to understand more about factors contributing to exam anxiety in undergraduate students. You design an online survey and send it out to the whole undergraduate mailing list for students at the UoM. The sample is comprised of individuals who complete the survey within a week of it being sent out.

Answer 36

Opportunity sampling

Question 37

Which of the following sampling methods is most free of bias? a. Snowball sampling b. Convenience sampling c. Systematic sampling d. Opportunity sampling

Answer 37

C

Question 38

It is often the case that as internal validity increases, __________________ decreases. a. internal consistency b. construct validity c. external validity d. content validity

Answer 38

C

Question 39

When our measure is not reflective of real world behaviour we have a problem with... a. Ecological validity b. Divergent validity c. Criterion validity d. Population validity

Answer 39

A

Question 40

Jen is conducting some research into attitudes about teenage pregnancy. She goes into a cafe on campus and ask the students there if they would mind completing her questionnaire. Jen is using... a. Stratified sampling b. Snowball sampling c. Cluster sampling d. Opportunity sampling

Answer 40

D