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AQA: Psychology Paper 2 > Research Methods > Flashcards

Research Methods Flashcards

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1
Q

Aim [definition]:

A

A statement of what the researcher intends to find out in a research study.
For example: Investigating the effect of caffeine on memory

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2
Q

Debriefing [definition]:

A

A post-research interview designed to inform participants of the true nature of the study and to restore them to the state they were at the start of the study

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3
Q

How is debriefing useful? [2]:

A
  • It is a means of dealing with ethical issues

- Can be used to get feedback on the procedures of the study

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4
Q

Independent variable [definition]:

A

The variable that changes in an experiment

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5
Q

Dependent variable [definition]:

A

Dependent on the independent variable

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6
Q

Control variable [definition]:

A

The one that doesn’t change

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7
Q

Confounding Variable [definition]:

A

A variable under the study that is not the IV but varies systematically with the IV

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8
Q

Extraneous variables [3]:

A
  • Do NOT vary systematically with the IV
  • They do not act as an alternative IV but instead have an effect on the DV
  • They are nuisance variables
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9
Q

Internal validity [definition]:

A

The degree to which an observed effect was due to the experimental manipulation rather than other factors such as confounding/extraneous variables

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10
Q

External validity [definition]:

A

The degree to which a research finding can be generalised to other settings (ecological validity)

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11
Q

Validity vs Reliability:

A 
Reliability = consistency of a measure 
Validity= accuracy of a measure
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12
Q

Confederate [2]:

A

An individual in a study who has been instructed how to behave, by the researcher
- In stanford prison experiment

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13
Q

Directional hypothesis [2]:

A
  • States the direction of the predicted difference between two conditions
  • example: Women will have higher scores than men will on Hudson’s self-esteem scale
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14
Q

Non-directional hypothesis [2]:

A
  • Predicts simply that there is a difference between conditions of the iv
  • There will be no difference between men’s scores and women’s scores on Hudson’s self-esteem scale
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15
Q

Pilot study [definition]:

A
  • A small-scale trial run of a study to test any aspects of the design, to make improvements before the final study
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16
Q

When do psychologists use a directional hypothesis?

A

When past research suggests that the findings will go in a particular direction

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17
Q

When is a non-directional hypothesis used?

A

When there is no past research on the topic studied or past research is contradictory

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18
Q

What are 3 types of experimental design?

A
  • Repeated measure design
  • Independent measure design
  • Matched pairs design
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19
Q

Repeated measures design [3]:

A

ALL participants experience ALL levels of the IV
+ Participant variables are reduced since its the same person
+ Fewer people are needed as they take part in all conditions

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20
Q

Limitations of repeated measure design [2]:

A
  • Order effects e.g getting tired. Can be avoided by using counterbalance
  • Participants may guess the aim of the experiment and behave a certain way e.g purposely do worse in the second half. Can be avoided by using a cover story
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21
Q

Independent measure design [2]:

A

Participants are placed in separate groups and only experience one level of the IV each
+ Avoids order effects

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22
Q

Limitations of independent measure design [2]:

A
  • Participant variables e.g different abilities or characteristics [participants are randomly allocated]
  • Needs more participants than repeated measure
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23
Q

Matched pairs design [3]:

A

Participants are matched by key characteristics or abilities, related to the study
+ Reduces participant variables
+ Reduces order effects

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24
Q

Limitations of matched pairs design [3]:

A
  • If one participant drops out you lose 2 PPs’ data
  • Very time-consuming trying to find closely matched pairs
  • Impossible to match people exactly
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25
Q

Lab experiments [2]:

A
  • Conducted in an environment controlled by researcher

- Researcher manipulates the IV

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26
Q

lab experiment examples [2]:

A
  • Milgram’s experiment on obedience

- Bobo’s doll

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27
Q

Strengths of lab experiments [2]:

A
  • It is easier to replicate. This is because standard procedure is being used
  • They allow for precise control of extraneous and independent variables
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28
Q

Weakness of lab experiments:

A
  • The artificiality of the setting may produce unnatural behavior that does not reflect real life (low ecological validity)
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29
Q

Field experiments [3]:

A
  • Conducted in the participant’s everyday setting
  • Researcher manipulates the IV, but in a real-life setting (can’t rlly control extraneous variables)
  • example: Hofling’s hospital study on obedience (involves medicine cabinet used by nurses in hospital and tested nurses)
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30
Q

Strengths of field studies [2]:

A
  • Behavior in a field experiment is more likely to reflect real life because of its natural setting
  • There is less likelihood of demand characteristics affecting the results, as participants may not know they are being studied (in covert experiments)
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31
Q

Weakness of field experiments [2]`:

A
  • There is less control over extraneous variables that might bias the results.
  • This makes it difficult for another researcher to replicate the study in exactly the same way.
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32
Q

Natural experiments [3]:

A
  • Conducted in everyday life
  • Researcher does NOT manipulate the IV cus occurs naturally
  • Hodges and Tizard’s attachment research (1989) compared the development of children who had been adopted to children who spent their lives with their biological families
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33
Q

Strengths of natural experiments [3]:

A
  • Behavior in a natural experiment is more likely to reflect real life because of its natural setting
  • There is less likelihood of demand characteristics affecting the results, as participants may not know they are being studied
  • Can be used in situations in which it would be ethically unacceptable to manipulate the independent variable, e.g. researching stress
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34
Q

Weaknesses of natural experiments [2]:

A
  • They may be more expensive and time consuming than lab experiments
  • There is no control over extraneous variables that might bias the results. makes it difficult replicate
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35
Q

Quasi experiments [3]:

A

+ Can be done in a controlled environment

  • IV is not made, it is a pre-existing difference
  • Sheridan and King 1972 tested obedience between the genders by making them shock a puppy with increasing strength. Male obedience was 54% and female was 100%
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36
Q

Strengths of quasi experiment:

A

Allows comparisons between different types of people

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37
Q

Weaknesses of quasi experiments [2]:

A
  • Participants may be aware they are being studied, creating demand characteristics
  • The dependent variable may be an artificial task reducing mundane realism
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38
Q

Mundane realism [definition]:

A

The degree to which the procedures in an experiment are similar to events that occur in the real world

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39
Q

Single blind design:

A

Participant is not aware of research aims and/or which condition of the iv they are in

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40
Q

Double blind design [2]:

A
  • Both participant and researcher are unaware of condition of IV or aim
  • The person conducting the experiment is less likely to give away the aim of the experiment
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41
Q

Experimental realism:

A

If the researcher makes an experimental task sufficiently engaging the participant pays attention to the task and not the fact that are being observed

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42
Q

Generalisation [definition]:

A

Applying the findings of a particular study to the population

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43
Q

Opportunity sample [3]:

A

People who are the most convenient or available are recruited
+ Easiest method cus u can just use the first suitable subject
- Biased sample cus only a small part of the population

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44
Q

Random sample [3]:

A

Uses random methods like picking names out of a hat
+ Unbiased/ all members of target population have an equal chance of getting chosen
- Time consuming (needs to have a list of all population members)

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45
Q

Stratified sample [3]:

A

Strata (subgroups) within a population are identified. Then members of the strata are chosen
+ More representative of the population than other samples
- Very time consuming

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46
Q

Systematic sample [3]:

A

A predetermined system is used to select participants
+ Unbiased as it uses an objective system
- Not truly random

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47
Q

Volunteer sample [3]:

A

Advertised on the newspaper, noticeboard or the internet and people volunteer
+ Gives access to variety of participants which can make the sample more representative
- Sample is biased because participants are more highly motivated to be helpful

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48
Q

Random techniques [3]:

A
  • Random number table
  • Random number generator
  • Lottery method (pulling names out of a hat)
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49
Q

Ethical issues [6]:

A
  • Deception
  • Informed consent
  • Privacy
  • Confidentiality
  • Protection from harm
  • Right to withdraw
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50
Q

Deception- Participant POV [3]:

A
  • It’s unethical.
  • The researcher should not deceive anyone without good cause.
  • Deception prevents informed consent
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51
Q

Deception- researcher’s POV [2]:

A
  • Can be necessary otherwise participants may alter behaviour
  • Can be dealt with by debriefing participant when study is completed
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52
Q

Informed consent- Participant POV [2]:

A
  • They should be told what will be required to do in the study so that they know what they are agreeing too
  • It is a basic human right
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53
Q

Informed consent- Researcher POV [2]:

A
  • Means revealing true aims of the study

- Can get presumptive consent

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54
Q

Right to withdraw- Participant POV [3]:

A
  • It is an important right
  • Allows patient to leave if uncomfortable
  • The withdraw may be compromised if payment was used as an incentive
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55
Q

Right to withdraw- Researcher POV [3]:

A
  • Can lead to a biased sample if people leave
  • They lose money if the person was paid and withdrew
  • Researcher has to inform the participant of this right before the study
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56
Q

Protection from harm- Participant POV [2]:

A
  • Nothing should happen to them during a study that causes harm
  • It is acceptable if the harm is no greater than what the subject would experience in ordinary life
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57
Q

Protection from harm- Researcher POV [3]:

A
  • Some more important questions in psychology involve a degree of distress to participants
  • It is difficult to guarantee protection from harm
  • Harm is acceptable if the outcome is more beneficial than the harm
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58
Q

Confidentiality- Participant POV [2]:

A
  • The data protection act makes confidentiality a legal right
  • It is only acceptable for personal data to be recorded if the data is not made available in a form that identifies participants
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59
Q

Confidentiality- Researcher’s POV [3]:

A
  • Can be difficult because the researcher wishes to publish the findings
  • A researcher can guarantee anonymity but it may still be obvious who the subjects were
  • Researchers should not record the names of participants
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60
Q

Privacy- Participant POV:

A
  • People do not expect to be observed in certain situations
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61
Q

Privacy- Researcher POV [2]:

A
  • It may be difficult to avoid invasion of privacy when studying participants in public
  • Do not study anyone without informed consent unless in a public place and displaying public behaviour
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62
Q

BPS ethical guideline strengths and weaknesses [3]:

A

+ The guidelines are quite clear

  • They’re vague
  • The guidelines absolve the individual responsibility because they can just justify their research claiming they followed the guidelines
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63
Q

Controlled observation [definition]:

A

A form of investigation in which behaviour is observed but under conditions where certain variables have been organised the researcher

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64
Q

Covert observations [definitions]:

A

Observing people without their knowledge.

Knowing that behaviour is being observed is likely to alter the participant’s behaviour

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65
Q

Inter-observer reliability [definition]:

A

The extent to which there is agreement between 2 or more observers involved in observations of a behaviour

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66
Q

Naturalistic observation [definition]:

A

An observation carried out in an everyday setting, in which the investigator does not interfere in anyway but merely observes the behaviours in question

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67
Q

Non-participant observation [definition]:

A

The observer is seperate from the people being observed

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68
Q

Overt observation [definition]:

A

Observational studies where participants are aware they are being observed

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69
Q

Participant observation [definition]:

A

Observations made by someone who is also participating in the activity being observed, which may affect their objectivity

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70
Q

Naturalistic observation evaluation [2]:

A

+ Gives a realistic picture of spontaneous behaviour (high ecological validity)
- There is little control of all other things that are happening (sumn unknown may cause the behaviour being observed)

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71
Q

Controlled observation evaluation [2]:

A

+ Observer can focus on particular aspects of behaviour

- control comes at the cost of the environment (artificial feeling)

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72
Q

Covert observation evaluation [2]:

A

+ Behaviour is more natural

- Participants cannot give consent

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73
Q

Overt observation [-]:

A
  • Participants are aware they are being watched and may behave unnaturally
74
Q

Participant Observation evaluation [3]:

A

+ May provide insight into behaviour from the ‘inside’

  • Likely to be overt and so have participant awareness issues
  • Might be biased
75
Q

Non-participant observation evaluation [2]:

A

+ Observers are likely to be more objective because they are not part of the group being observed
- More likely to be covert and so there is ethical issues

76
Q

Event sampling [definition]:

A

An observational technique in which a count is kept of the number of times a certain behaviour occurs

77
Q

Time sampling [definition]:

A

An observational technique in which the observer records behaviours in a given timeframe

78
Q

Structured interview [definition]:

A

Any interview with predetermined questions

79
Q

Unstructured interview [definition]:

A

The interview starts with some general aims and possibly some questions, and lets the interviewee’s guide subsequent questions

80
Q

Questionnaire evaluation [3]:

A

+ Can reach large numbers of people easily (large sample)
+ Respondents may be more willing to give personal information in a questionnaire than an interview
- can only be filled by literate people = sample is biased

81
Q

Structured interview evaluation [4]:

A

+ Can be easily repeated cus questions are standardised
+ Easier to analyse than unstructured interview
- low reliability: different interviewers behave differently
- Interviewer bias

82
Q

Unstructured interview evaluation [3]:

A

+ more detailed information than in structured

  • Require interviewers with more skill than structured
  • In-depth questions may lack objectivity compared to predetermined ones
83
Q

Correlation [definition]:

A

A relationship between two variables

84
Q

Correlations [3]:

A
  • Participant provides data for both variables
  • In a correlation design, there are no independent or dependent variables, but co-variables
  • We only use a correlation when testing the relationship between 2 variables
85
Q

Structured observation [definition]:

A

A researcher uses various systems to organise observation such as behavioural categories and sampling procedures

86
Q

What happens in unstructured observations?

A

The researcher records all relevant behaviour but has no system

87
Q

Features of structured observations [2]:

A
  • Behavioural categories

- Time/event sampling

88
Q

Rules of behavioural categories [3]:

A
  • Categories should be objective
  • Cover all possible component behaviours
  • Categories should be mutually exclusive
89
Q

What are the self report techniques [3]:

A
  • Structured interview
  • Unstructured interview
  • Questionnaire
90
Q

Rules of writing a questionnaire [3]:

A
  • Questions must be clear
  • Bias can lead to a participant to give a particular answer
  • Questions need to be written so that answers are easily to analyse
91
Q

What to add in a questionnaire [2]:

A
  • Filler questions to distract participant from true aim

- Easier questions first

92
Q

Meta analysis [definition]:

A

When a researcher looks at findings from a number of different studies and produces a statistic to represent the overall effect

93
Q

Review [definition]:

A

A consideration of a number of studies that have investigated the same topic in order to reach a general conclusion about a particular hypothesis

94
Q

Content analysis [definition]:

A

A type of observational study where behaviour is observed INDIRECTLY in written or verbal materials (interviews, questionnaires)

95
Q

Effect size [definition]:

A

A measure of the strength of the relationship between two variables

96
Q

Meta analysis strengths [2]:

A

+ Increases validity of conclusion as they are based on wider sample of participants
+ Groups of studies on same topic often contradict, meta analysis helps us to reach an overall conclusion with stats

97
Q

Limitations of meta analysis [2]:

A
  • Experimental designs in different studies may vary so research will never be truly comparable
  • Putting them all together to calculate the effect size may not be appropriate
98
Q

Why is the mean the most sensitive measure of central tendency? *

A

It takes account of the exact distance between all the values of data

99
Q

When is a scattergram used in psychology?

A

When correlations lol

100
Q

When is a line graph used in psychology?

A

With continuous data

101
Q

When is a histogram used in psychology?

A
  • Can’t draw histogram with data in categories

- When frequency is mentioned lmao

102
Q

When is a bar chart used in psychology? [2]:

A
  • When data is not continuous

- Can be used when categorical / nominal data

103
Q

When is a table used in psychology?

A

when displaying raw data

104
Q

Skewed distribution [definition]: *

A

There is a number of extreme values on one side

105
Q

Positive skewed distribution =

A

Scores on the left side

106
Q

Negative skewed distribution =

A

Scores to the right side

107
Q

Quantitative data =

A

numbers n shiiii

108
Q

Qualitative data =

A

cannot be quantified

109
Q

Quantitative data evaluation [2]:

A

+ Easy to analyse using descriptive stats or stats tests

- Data may oversimplify reality

110
Q

Qualitative data [2]:

A

+ Provides richer and detailed information about people’s experiences
- Complexity makes it more difficult to analyse/summarise and draw conclusions from

111
Q

Primary data evaluation [2]:

A

+ researcher has control of the data and how it is collected
- Lengthy and expensive process

112
Q

Secondary data [definition]:

A

Information used in research that was collected by someone else

113
Q

Secondary data evaluation [2]:

A

+ It is simpler and cheaper to access someone else’s data

- Data may not exactly fit the needs of the study

114
Q

When is a sign test used? [3]:

A
  • Paired or related data
  • Repeated measure design
  • matched pair design
115
Q

How to sign test:

A

s value = no. of smallest sign

116
Q

Nominal data [definition]:

A

Named data which can be separated into discrete categories which do not overlap

117
Q

Ordinal data [definition]:

A

Data which is placed into some kind of order or scal

118
Q

Interval data [definition]:

A

Data which comes in the form of a numerical value where the difference between points is standardised and meaningful

119
Q

What are the types of data? [4]:

A
  • Nominal data
  • Ordinal data
  • Interval data
  • Ratio
120
Q

Peer review evaluation

A

*

121
Q

Content analysis [definition]:

A

A type of observational study where behaviour is observed indirectly in visual or verbal material

122
Q

Thematic analysis [explanation]:

A

Themes or categories are identified and data is organised into these themes

123
Q

Content analysis [3]:

A
  • Researcher has to pick whether they are using a time or event sample
  • Then have to pick behavioural categories for them to tally
  • Represent data by analysing data quantitatively or qualitatively
124
Q

Example of quantitative content analysis [4]:

A
  • Anthony Manstead & Caroline McCulloch
  • Interested in the way men and women were presented in tv ads
  • observed 170 ads over one week
  • Focused on adult figure & recorded frequency of desired behaviour in a table
125
Q

Thematic analysis [3]:

A
  • qualitative content analysis
  • quali data summarised by identifying repeated themes
  • Very lengthy process cus every thing is heavily analysed
126
Q

Strengths of content analysis [2]:

A

+ have high ecological validity cus its based on observations of what people acc do
+ Content analysis can be replicated cus sources can be accessed by others

127
Q

Weaknesses of content analysis [2]:

A
  • Observer bias reduces OBJECTIVITY & VALIDITY of findings cus different observers may interpret behavioural categories differently
  • likely to be culturally biased cus observer is judging behaviours based on their standards
128
Q

What are the intentions of thematic analysis? [3]:

A
  • to impose some kind of order on data
  • summarise data to reduce page no.
  • ensure that ‘order’ is representative
129
Q

Case study [2]:

A
  • detailed study of an individual

- provide a rich record of human experience

130
Q

Case study example [3]:

A
  • Henry Molaison: his hippocampus was removed cus epi seizures, can’t form new memories
  • Little Hans
  • Phineas Gage: iron rod through brain
131
Q

Case studies strengths [2]:

A

+ ideographic- in-depth data provides new insights

+ Allow us to investigate rare instances of human behaviour e.g Romanian orphanages

132
Q

Case studies weaknesses [2]:

A
  • Difficult to generalise/ apply to population

- ethical issues like confidentiality and informed consent, protection from harm

133
Q

Inter-observer reliability [definition]:

A

The extent to which there is an agreement between two or more observers in an experiment

134
Q

Test-retest reliability [definition]:

A

same test or interview is given to same participant on diff occasion to see if they get the same result

135
Q

How to asses reliability [3]:

A
  • Have 2 or more observers making separate records and then compare
  • inter-observer- reliability is the extent they agree
  • calculated using correlation coefficients
136
Q

Improving inter-observer reliability [2]:

A
  • Clearer behavioural categories (may not have been clear before)
  • Observers may need more practice using the categories
137
Q

Improving reliability [2]:

A
  • Reduce ambiguity of items in tests

- Standardise procedure

138
Q

Concurrent validity [definition]:

A

establishing validity by comparing an existing test with the one ur interested in

139
Q

Ecological validity [definition]:

A

ability to generalise research effect beyond the research setting

140
Q

Face validity [definition]:

A

the extent which test items look like what the test claims to measure

141
Q

Mundane realism [definition]:

A

How a study mirrors the real world/ is it realistic?

142
Q

Temporal validity [definition]:

A

whether research can be generalised beyond the time period of the study

143
Q

Validity [definition]:

A

whether an observed effect is a genuine one

144
Q

How to improve validity [2]:

A
  • If face = make better questions bro

- If internal/ external = use better research design bro smh

145
Q

What are the features of science? [5]:

A
  • Empirical methods
  • Objectivity
  • Replicability
  • Theory construction
  • Hypothesis testing
146
Q

What are empirical methods?

A

When info is gained thru observation or experimentation rather than unfounded beliefs

147
Q

Theory construction [explanation]:

[2]:

A

Facts alone are meaningless, theories/ explanations must be made to make the facts make sense
- can be done through hypothesis testing

148
Q

Falsifiablility [definition]:

A

The possibility that a statement or hypothesis can be proven wrong

149
Q

Type 1 error [definition]:

A

When a researcher rejects a null hypothesis that’s true

150
Q

Type 2 error [definition]:

A

When a researcher accepts a null hypothesis that is not true

151
Q

When is p ≤ 0.01 used?

A

When a researcher is replicating another study because results need to be more certain

152
Q

What is a parametric test? [3]:

A
  • A test that has interval data or ratio level of measurement.
  • Be drawn from population with normal distribution.
  • Both samples have equal variances.
153
Q

Non- parametric tests of difference [4]:

A
  • Wilcoxon test
  • Mann-whitney
  • Sign test
  • Chi-square
154
Q

Parametric tests of difference [2]:

A
  • Related t test

- Unrelated t test

155
Q

Tests of correlation [2]:

A
  • Spearman’s Rho (non-parametric)

- Pearson’s R (parametric)

156
Q

Wilcoxon test [3]:

A
  • Hypothesis states a difference
  • Related data (repeated measure/ matched pairs)
  • Ordinal data
157
Q

Wilcoxon significance [2]:

A
  • Calculated value of ‘T’ must be ≤ than the critical value to be significant
  • If not significant we accept the null
158
Q

Mann-Whitney [3]:

A
  • Hypothesis states a difference
  • Unrelated data (independent measure)
  • Ordinal data
159
Q

Mann-Whitney significance [2]:

A
  • Calculated value of ‘U’ must be ≤ than the critical value to be significant
  • If not significant we accept the null
160
Q

Related t- test [3]:

A
  • Hypothesis states a difference
  • Related data (repeated measure/ matched pairs)
  • Interval data
161
Q

Related t-test significance [2]:

A
  • Calculated value of ‘t’ must be ≥ than the critical value to be significant
  • If not significant we accept the null
162
Q

Unrelated t-test [3]:

A
  • Hypothesis states a difference in data
  • Unrelated data (independent measure)
  • Interval data
163
Q

Unrelated t-test [2]:

A
  • Calculated value of ‘t’ must be ≥ than the critical value to be significant
  • If not significant we accept the null
164
Q

Spearman’s Rho [3]:

A
  • Hypothesis states a corrrelation
  • Related data (repeated measure/ matched pairs)
  • Ordinal data
165
Q

Spearman’s Rho significance [2]:

A
  • Calculated value of ‘rho’ must be ≥ than the critical value to be significant
  • If not significant we accept the null
166
Q

Pearson’s R [3]:

A
  • hypothesis states a correlation
  • Related data (repeated measure/ matched pair)
  • Interval data
167
Q

Pearson’s R significance [2]:

A
  • Calculated value of ‘r’ must be ≥ than the critical value to be significant
  • If not significant we accept the null
168
Q

Chi square [3]:

A
  • Hypothesis states a difference/ association
  • Unrelated/ independent data
  • Nominal data
169
Q

Chi square significance [2]:

A
  • Calculated value of ‘x2’ must be ≥ than the critical value to be significant
  • If not significant we accept the null
170
Q

Sign test [3]:

A
  • Hypothesis states a difference
  • Related data (repeated measure/ matched pairs)
  • Nominal data
171
Q

Sign test significance [2]:

A
  • Calculated value of ‘S’ must be ≤ than the critical value to be significant
  • If not significant we accept the null
172
Q

One-tailed test [definition]:

A

Form of test used with a directional hypothesis

173
Q

Two-tailed test [definition]:

A

Form of test used with a non-directional hypothesis

174
Q

Degrees of freedom

A

*

175
Q

levels of measurement =

A

ration , nominal , ordinal , interval

176
Q

Report structure [6]:

A
  1. abstract
  2. intro
  3. Method
  4. results
  5. discussion
  6. references
177
Q

What is an abstract?

A

A summary of the study e.g aims, hypothesis method

178
Q

what measure of central data is used for nominal data?

A

Mode

179
Q

what measure of central data is used for ordinal data?

A

Median

180
Q

what measure of central data is used for interval/ratio?

A

Mean

181
Q

What is the order of robustness for the measures of central tendency?

A
  1. Mean
  2. Median
  3. Mode

AQA: Psychology Paper 2 (3 decks)

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