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AO3 Flashcards

1
Q

Strengths of independent groups (2)

A

-Order effects are not a problem (they are for repeated groups)​.
-Participants are less likely to guess the aim, less chance of demand characteristics.

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2
Q

Weakness of independant groups (1)

A

The participants who occupy the different groups are not the same in terms of participant variables. These differences may act as cofounding variables, reducing validity of findings

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3
Q

Strengths of repeated measures (2)

A

-Participant variables are controlled – higher validity.​
-Fewer participants are needed, less time/effort recruiting them

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4
Q

Weakness of repeated measures (1)

A

Order effects apply as each participant has to do at least two tasks, the order ay be significant to the results

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5
Q

Counterbalancing

A

Attempt to control order effects ( half the participants do condition A, then B. The other half do condition B, then A.

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6
Q

Strengths of matched pairs (1)

A

Participants only take part in a single condition so order effects and demand characteristics are less of a problem

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7
Q

Weakness of matched pairs (1)

A

Less economical – is expensive and time-consuming, especially when pre-test is required

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8
Q

Strengths of lab experiments (3)

A

-High control over variables​
-Easier to replicate​
-Higher internal validity due to control over extraneous variables

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9
Q

Weakness of lab experiments (3)

A

-Lacks generalisability​
-Demand characteristics ​
-Artificial tasks – lacks mundane realism

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10
Q

Strengths of field experiments (2)

A

-Higher mundane realism than lab​
-Fewer demand characteristics

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11
Q

Weakness of field experiments (2)

A

-Loss of control over extraneous variables​
-More difficult to establish cause and effect between IV and DV

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12
Q

Strengths of natural experiments (2)

A

-Unethical research can be done (eg Romanian Orphan Study)​
-Natural behaviour in a natural environment – high external validity and mundane realism

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13
Q

Weakness of natural experiments (2)

A

-Event can happen very rarely or be a one-off occurrence – poor generalisability​
-We cannot allocate participants to the conditions – risk of participant variables acting as extraneous or cofounding variables

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14
Q

Strengths of quasi experiments (1)

A

Highly controlled (like lab experiments)

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15
Q

Weakness of quasi experiments (1)

A

Cannot allocate participants randomly – risk of participant variables affecting results

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16
Q

Strengths of naturalistic observations (1)

A

High ecological validity - results can be generalised as behaviour is studied in an environment where it would normally occur

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17
Q

Weakness of naturalistic observations (1)

A

Lack of control over extraneous variables which means replication is difficult

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18
Q

Strengths of controlled observations (2)

A

Can be replicated easily due to standardised procedures. Findings can be checked to see if they occur again, easier to control extraneous variables​
​

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19
Q

Weakness of controlled observations (1)

A

Lower external validity as behaviour may be contrived as a result of the setting

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20
Q

Strengths of covert observations (1)

A

Demand characteristics are reduced, and natural behaviour increases validity

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21
Q

Weakness of covert observations (1)

A

Unethical, no consent and may be invading privacy

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22
Q

Strengths of overt observations (1)

A

Ethical as participants are aware they’re being observed

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23
Q

Weakness of overt observations (1)

A

Knowledge of being studied influences behaviour – reduces internal validity

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24
Q

Strengths of non-participant observations (1)

A

Observer remains an objective distance so less chance of bias results

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25
Weakness of non-participant observations (1)
May lose valuable insight as they are too far removed from people and behaviour they are studying
26
Strengths of participant observations (1)
Lead to greater insight, researcher experiences the situation as the participants do, enhancing external validity
27
Weakness of participant observations (1)
Researcher may lose objectivity as they identify too strongly with the group they are observing (Zimbardo)
28
Strengths of structured observational designs (1)
Makes recording of data easier and more systematic​ Quantitative data is easier to analyse
29
Weakness of structured observational designs (1)
Rely on a list of predetermined categories and the categories chosen may not cover all behaviours observed
30
Strengths of unstructured observational designs (2)
Provides a great deal of rich, qualitative data​ Qualitative data is more difficult to record and analyse
31
Weakness of unstructured observational designs (1)
Greater risk of observer bias – researcher only observes behaviour that 'catches their eye'
32
Strengths of time sampling (2)
Reduces number of observations, provides discrete data​
33
Weakness of time sampling (2)
May be unrepresentative, the researcher may miss important details outside of the timescale
34
Strengths of event sampling (1)
Useful for infrequent behaviour as the researcher will pick up behaviours that do not occur at regular intervals
35
Weakness of event sampling (1)
Complex behaviour may be over-simplified as important details may go unrecorded – decreases validity
36
Strengths of questionnaires (3)
-Cheap to make and distribute quickly​ -Can distribute to a large number of people​ -Easy to analyse, trends and patterns can be established – quantitative data
37
Weakness of questionnaires (4)
-Social desirability bias – respondents won't always be truthful​ -Risk of low response rate if there is not a large sample size due to people not completing it​ -Quantitative data doesn't always allow elaborated data and does not gain a deeper insight​ -Response bias as respondents may complete the questionnaire too quickly/fail to read the questions properly
37
Weakness of open questions (1)
Qualitative data is harder to analyse
38
Strengths of open questions (3)
-Produce qualitative data ​ -Rich in detail and description​ -Elaborates/tells us why
39
Strengths of closed questions (3)
-Produces quantitative data ​ -Easy to analyse​ -Can be displayed on graphs/charts
40
Weakness of closed questions (2)
-Lacks depth and detail​ -Doesn't give us context
41
Strengths of structured interviews (2)
-High reliability due to standardised procedures​ -Quick as it does not require specialised training
42
Weakness of structured interviews (2)
-Lacks validity as interviewer cannot probe for detail and questions are usually closed ​ -Not suitable for sensitive topics as interviewer and interviewee cannot build a rapport
43
Strengths of unstructured interviews (2)
-Flexible as researcher can deviate from questions and can follow up on certain answers​ -High validity as researcher can probe for detail and participants are allowed to elaborate
44
Weakness of unstructured interviews (3)
-Lacks reliability as there are not set questions to follow​ -Time consuming as researchers need to be trained​ -Difficult to analyse because it is qualitative data
45
Strengths of qualitative data (1)
-Broader and more detailed information gathered
46
Weakness of qualitative data (2)
-Difficult to analyse and summarise​ -Relies on the subjective interpretation of the researcher
47
Strengths of quantitative data (1)
-Simple to analyse, more objective and easier to compare data
48
Weakness of quantitative data (2)
-Less detail​ -Fails to represent 'real life' - poor external validity
49
Strengths of primary data (1)
-It is collected specifically for the purpose of the investigation
50
Weakness of primary data (1)
-Takes a lot of time/energy/money to collect
51
Strengths of secondary data (1)
-Inexpensive, requires minimal effort to obtain
52
Weakness of secondary data (1)
-Accuracy of data is questionable – might be incomplete, outdated or not fit for the purpose of the investigation
53
Strengths of correlations (2)
-Quick and easy starting point. Quick and easy to run as you do not manipulate variables and you can use secondary data ​ -Reliable as it can be tested for – to check it is reliable you run the same correlation at a different time
54
Weakness of correlations (2)
-Cause and effect. You cannot say that one causes the other, just that there is a relationship​ (it may be a 3rd variable that affects both other variables)​ -Lack of validity as it reduces rich, qualitative data to numerical values – reduces bigger picture
55
Strengths of mean (1)
The most 'sensitive' measure as it includes all scores in data set – more representative​
56
Weakness of mean (1)
Easily distorted by extreme values
57
Strengths of median (1)
Not affected by extreme scores
58
Weakness of median (1)
Less sensitive than the mean - doesn't include all data in the set
59
Strengths of mode (2)
Very easy to calculate​ Sometimes the only one that can be used
60
Weakness of mode (1)
Not representative – doesn't include all data in a set
61
Strengths of range (2)
Easy to calculate, easy in general​ Simple formula​ ​
62
Weakness of range (1)
Does not account for the distribution of the scores
63
Strengths of standard deviation (1)
Includes all values within the calculation, more accurate picture of the overall distribution of data set
64
Weakness of standard deviation (1)
May be misleading as it can be distorted by extreme values
65
Strengths of random sampling (2)
Free from researcher bias ​ Likely to produce a sample that is more representative than an opportunity or volunteer sample​
65
Weakness of random sampling (2)
Time consuming to conduct​ Some participants may refuse to take part, so you end up with more of a volunteer sample
66
Strengths of systematic sampling (1)
Free from researcher bias​
67
Weakness of systematic sampling (1)
Some participants may refuse to take part, so you end up with more of a volunteer sample​
68
Strengths of stratified sampling (2)
-Free from researcher bias​ -Produces an accurate, proportionally representative sample – good generalisation ​
69
Weakness of stratified sampling (1)
Only 1 or 2 strata can be identified – sample may not be fully representative
70
Strengths of opportunity sampling (1)
Convenient and saves time ​
71
Weakness of opportunity sampling (2)
-Unrepresentative as samples come from one area ​ -Researcher bias – may not approach people that seem unapproachable
72
Strengths of volunteer sampling (2)
-Quick and easy​ -Little effort necessary​
73
Weakness of volunteer sampling (1)
Volunteer bias – a certain 'type' of person (university, broke, unemployed) may be likely to respond

Research Methods (1 decks)

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