Week 2 - Variables, Sampling, Validity, and Reliability

Question 1

Population

Answer 1

Universe of all units from which sample is selected

Question 2

Sample

Answer 2

Segment of population selected for investigation

Question 3

Sampling Frame

Answer 3

A list of all members/elements in the population from which you can obtain a sample

Question 4

Census

Answer 4

All members of a population are considered

Question 5

Statistic

Answer 5

A numerical characteristic of sample data

Question 6

Parameter

Answer 6

A numerical characteristic of population data

Question 7

Sampling error

Answer 7

The difference between the value of the sample statistic and the value of the population mean, population standard deviation

Question 8

Response rate

Answer 8

The percentage of individuals selected to be in the sample who participate in the study

Question 9

Probability vs Non-Probability Sampling

Answer 9

Quantitative = generally probability samples
Qualitative = generally non-probability samples

Question 10

Probability Sampling

Answer 10

A way to ensure that your sample is representative of the population- members of the population have an equal chance of being selected in the sample

Question 11

Types of Probability Sample

Answer 11

• Simple random sample
• Systematic random sample
• Stratified random sampling
• Multistage cluster sampling

Question 12

Simple Random Sample

Answer 12

Each member has an equal and independent chance of being selected

Question 13

Systematic Random Sample

Answer 13

Every xth person - Randomly select the first person then divide the size of the population by the size of the desired sample and use this to determine the interval at which sample is selected

Question 14

Stratified Sampling

Answer 14

Researcher divides population into subpopulations (strata) and random sample from the strata

Question 15

Multi-stage Cluster Sampling

Answer 15

Begin with a sample groupings and then sample individuals

Question 16

Advantages of Probability Sampling

Answer 16

Helps overcome sampling bias

Question 17

Non-Probability Sampling

Answer 17

Not every member of the population has an equal chance of being part of the sample

Question 18

Types of non-probability sampling

Answer 18

• Convenience Sample
• Snowball Sampling
• Quota Sampling
• Purposive/judgement Sampling

Question 19

Convenience Samples

Answer 19

A sample of available participants

Question 20

Snowball Sampling

Answer 20

Used mainly for hard to study populations - Collecting data with members of the population that can be located and then asks those members to provide information/contacts for other members of the population

Question 21

Quota Sampling

Answer 21

Equivalent to stratified random sample

Question 22

Purposive/Judgement Sampling

Answer 22

Selecting a sample based on knowledge of the population, its elements, and the purpose of the study

Question 23

Operationalisation

Answer 23

The things put in place to measure a variable

Question 24

Reliability & Validity

Answer 24

Applies mostly to indexes/scales - cannot be assessed until after questionnaires have been developed and used

Question 25

Validity

Answer 25

Are we measuring what we think we are measuring?

Question 26

Types of Validity

Answer 26

• Face validity
• Content validity
• Criterion validity
• Construct validity

Question 27

Face Validity

Answer 27

Does my measure seem to relate to the construct

Question 28

Content Validity

Answer 28

The extent to which the measure represents a balanced adequate sampling of relevant dimensions

Question 29

Criterion-related Validity

Answer 29

Involves checking the performance of your measure against some external criterion
Two types:
Concurrent
Predictive

Question 30

Concurrent Validity

Answer 30

Establish the validity of your measure by comparing it to a ‘gold standard’

Question 31

Predictive Validity

Answer 31

Does the measure predict something that it’s theoretically supposed to predict

Question 32

Construct Validity

Answer 32

Establishes validity by showing that your measures related to other constructs in a way that you would expect
Two types:
Convergent
Divergent (discriminant)

Question 33

Convergent validity

Answer 33

Measures of constructs that theoretically should be related to each other, are, in fact observed to relate to each other

Question 34

Divergent validity

Answer 34

Measures of constructs that theoretically should not be related to each other, are, in fact, observed not to relate to each other

Question 35

Reliability

Answer 35

The consistency or repeatability of your measurement

Question 36

Types of Reliability

Answer 36

• Stability of the measure (test-retest)
• Internal consistency of the measure (split-half, Cronbach’s alpha)
• Agreement of consistency across raters

Question 37

Test-retest reliability

Answer 37

Addresses the stability of your measure by measuring at one point in time and again at a later point in time

Question 38

Split half reliability

Answer 38

Administer a single measure at one time to a group of Ps but split measure into two halves, correlate scores of two halves (higher correlation = higher reliability)

Question 39

Cronbach’s alpha

Answer 39

Assesses the internal consistency of your measure

Question 40

Inter-rater or inter-observer reliability

Answer 40

Checking the match between two or more raters or judges