research methods Flashcards

1
Q

aim

A

a general statement of what the researcher intends to study

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2
Q

hypothesis

A

a prediction of what the researcher thinks will happen in their study

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3
Q

directional hypothesis

A

states the direction of the difference or relationship

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4
Q

non-directional

A

does not state the direction of the difference or relationship.
the researcher says there will be a difference but doesn’t elaborate further.

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5
Q

null hypothesis

A

states there will be no difference in the direction or relationship

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6
Q

operationalisation

A

clearly defining variables in terms of how they are measured.

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7
Q

extraneous variables

A

any other variables apart from the IV that might have an effect on the DV.

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8
Q

types of EV

A

participant variable eg age
situational variable eg noise
experimenter variable eg appearance

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9
Q

confounding variable

A

any other variables apart from the IV that does have an effect on your DV

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10
Q

laboratory experiments

A

conducted in highly controlled environment. researcher has high levels of control over the IV and DV.

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11
Q

strengths of laboratory experiments

A

high control over all variables - allows cause + effect relationship to be established.
easily replicable which allows you to determine whether your results are reliable as it uses standardised procedures

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12
Q

limitations of lab experiments

A

artificial environment so lack of ecological validity - cannot be generalised to everyday life.
demand characteristics - when a participant changes their behaviour because they know they are part of research .

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13
Q

Field experiments

A

Real life setting.
IV is manipulated and effect on DV is measured

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14
Q

Strengths of field experiments

A

Real life environment so high levels of ecological validity
Lower levels of demand characteristics - higher validity

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15
Q

Limitations of field experiments

A

Less control over EVs so difficult to establish cause and effect relationship
Hard to replicate due to lack of standardised procedures
Ethical issues - participants unaware they’re part of study so lack of informed consent

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16
Q

Natural experiments

A

Real life settings
IV changes naturally and effect it has on DV is measured

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17
Q

Strengths of natural experiments

A

Often able to study events that would not be ethically or practically possible

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18
Q

Limitations of natural experiments

A

Some experiments are rare so difficult to replicate. This lowers reliability
Lees control over EVs makes it difficult to establish cause + effect relationship

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19
Q

Quasi experiments

A

In a controlled setting
IV hasn’t been chosen by researcher. It is fixed and cannot be manipulated
Eg. You can’t change a persons age

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20
Q

Strengths of Quasi experiments

A

high control over all variables - allows cause + effect relationship to be established.
easily replicable which allows you to determine whether your results are reliable as it uses standardised procedures

21
Q

Limitations of quasi experiments

A

artificial environment so lack of ecological validity - cannot be generalised to everyday life.
demand characteristics - when a participant changes their behaviour because they know they are part of research .

22
Q

Target population

A

A large group of people the researcher is interested in studying

23
Q

Representative

A

A sample that reflects the target population

24
Q

Generalisation

A

The extent to which findings can be broadly applied to the population

25
Opportunity sampling
Recruit people who are most available to use. Eg people in street Produces an unrepresentative sample
26
Strengths of opportunity sampling
Convenient - little time spent gathering sample Cost effective
27
Limitations of opportunity sampling
Researcher bias Bias- when/were you collect sample may affect representativeness
28
Random sampling
Each member of target population has equal chance of being chosen Produces representative sample ‘Lottery method’
29
Strengths of random sampling
No researcher bias
30
Limitations of random sampling
Time consuming ‘Freak sample’ - you could still end up with unrepresentative sample
31
Stratified sampling
Subgroups within a population are selected eg boys and girls Need to identify strata that make up target population
32
Strengths of stratified sampling
No researcher bias
33
Limitations of stratified sampling
Sometimes impossible- not all identified strata within population can be represented in sample
34
Systematic sampling
Use a predetermined system to select participants eg every nth participant
35
Strengths of systematic sampling
No researcher bias
36
Limitations of systematic sampling
‘Freak sample’
37
Volunteer sampling
Participants select themselves to take part in study Ad in newspaper
38
Strengths of volunteer sampling
Easy sample for researcher Cost effective
39
Limitations of volunteer sampling
Volunteer bias No sample - no one might respond to ad
40
Independent groups
Participant only takes part in 1 condition
41
Strengths of independent groups
Not affected by order effects Not affected by demand characteristics - less chance they will guess aim / change behaviour
42
Limitations of independent groups
More participants - time consuming Individual differences of participants
43
Repeated measures
Participant takes part in both conditions
44
Strengths of repeated measures
No individual differences Fewer participants
45
Limitations of repeated measures
Order effects Demand characteristics
46
Matched pairs
Matched in terms of age, IQ etc Participant A does condition 1, B does condition 2
47
Strengths of matched pairs
No order effects Lees likely to be affected by demand characteristics Less individual differences
48
Limitations of matched pairs
More participants needed - time consuming Matching people is difficult
49
How to overcome issues with experimental designs
Random allocation - tries to control individual differences in participants. Each P has equal chance of being allocated either condition Names on paper and pulled out hat Counter balancing - controls order effects. Half do condition 1 first other half do other