Week 1 - intro to key terms

Question 1

What is the difference between induction, and deduction?

Answer 1

Induction = is a subjective interpretation (not concerned with generalisability) (Interpretivist)

deduction = based on objective data –> to specific phenomenon

Question 2

What is the difference between categorical and continuous variables? Provide examples.

Answer 2

Categorical variables are nominal (by name) = e.g. age, religion, gender.

Continuous variables = vary by degree (e.g. height, reaction time, anxiety levels).

Question 3

What is the difference between extraneous variables, and confounding variables?

Answer 3

Extraneous variables are also known as nuisance variables. Can be any other factor that may effect results of the study.

Confounding variables are a third variable, that is systematically related to the IV. Therefore, any changes in the DV cannot be directly/ exclusively related to the IV due to a third confounding variable.

Question 4

What is the difference between a mediating and moderating variable?

Answer 4

Mediating variables determine the outcome between two variables - e.g. a = b which produces c.

Moderating variable causes one variable to become dependent on another. E.g. anxiety impacts memory, which is effected by age. (Age is moderating variable).

Question 5

Describe the ways in which you can manipulate your variable.

Answer 5

Individual difference (might naturally occur: e.g. uni degree, age, height)
Experimental manipulation (might randomly assign participants to groups) 

Between groups (comparing two groups)
Within groups (comparing differences within groups) 
Mixed design (might be more than one IV, both with two levels of manipulation = factorial design)

Question 6

Define these sampling techniques: simple random, systematic random, stratified sampling not a cluster, multi-stage cluster sampling.

Answer 6

simple random = every member of the population have equal chance of being selected
systematic random = every Xth person
stratified sampling = taking different clusters and choosing random sample from each cluster
multi-stage cluster = taking different clusters, and selecting a few clusters to sample from (not each group has to be represented).

Question 7

Describe convenience, snowball, and purposive sampling.

Answer 7

Convenience sampling = most convenient to access, also money efficient.
Snowball sampling = flow on effect; e.g. friends of friends become involved. Helpful for risky groups.
Purposive sampling = targeted, more clear purpose.

Question 8

What is external validity?

Answer 8

Good external validity means a study can be generalised to the broader population

Question 9

What is internal validity?

Answer 9

Internal validity means the study has been measured and operationalised in a way that best describes the relationship of the variables/ phenomenon of interest. However, although internal validity might be high (e.g. a very controlled experiment), this might reduce the external validity of a study.

Question 10

What is face validity, VS content validity?

Answer 10

Face validity means from the outside, or perspective of others, the study is describing the phenomenon well - items appear to relate to the construct.

Content validity = means the study captures all elements of a construct (entire meaning).

Question 11

What is a criterion validity, and its two subgroups?

Answer 11

Criterion validity means the study or measures agree with an external source: (e.g. adequate scales)
Con-current - agrees with gold standard
Predictive - agrees with future behaviour

Think of CRITERIA! We use criteria to determine which scales we will employ in our study.

Question 12

What is a construct validity, and its two subgroups?

Answer 12

How well multiple indicators relate to each other - showing that your measure relates to another construct, in the way you would expect.

Convergent (construct validity) = constructs that relate to each other, and do. (COME together: converge)
Divergent = measure does not correlate with something that it shouldn’t (DIVIDE: divergent)

Question 13

Define reliability.

Answer 13

The consistency and repeatability of your measurement.

Question 14

What is test-retest reliability?

Answer 14

addresses stability of measure over time. (point 1 & point 2) - should be relationship observed.

Problems:

• practice effect
• long intervals / too short, effects memory or there could be a historical event.

Question 15

What is split half reliability?

Answer 15

administered at a single time, however measure/ Q split in half. Then these two halves are correlated with each other.

Question 16

What is cronbachs alpha?

Answer 16

It tests the validity / internal consistency of your measure.

Question 17

What is inter-rater/observer reliability?

Answer 17

checks match between two or more raters (judges) - need to make sure coders are consistent.