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GCSE Psychology (AQA) 2024 > Research Methods > Flashcards

Research Methods Flashcards

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1
Q

theory

A

explanation for behaviour, tested using objective research methods

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2
Q

aim

A

general statement explaining the purpose of a study (to investigate)

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3
Q

independent variable

A

deliberately changed

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4
Q

dependent variable

A

what is being measured

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5
Q

operationalisation

A

making variables clearly defined and measured

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6
Q

hypothesis

A
  • clear and precise testable statement

- states the relationship between the variables being investigated

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7
Q

hypothesis

A

statement of a relationship between variables (there is a difference)

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8
Q

null hypothesis

A

statement of no relationship between variables (there is no difference)

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9
Q

cause and effect

A

the only thing that should cause a change in the DV is the IV

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10
Q

extraneous variables

A
  • unwanted “extra variables” that may interfere with the relationship between the IV and DV
  • can affect DV
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11
Q

what happens if extraneous variables aren’t controlled?

A

the researcher cannot truly know what caused the change in the DV

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12
Q

why are research procedures enforced?

A

its important to design studies in a systematic way in order to control possible extraneous variables

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13
Q

requirements for instructions to participants

A
  • all participants must receive exactly the same information throughout an investigation (standardised)
  • this ensure that what is said to participants doesn’t act as an EV
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14
Q

standardised procedures

A
  • using the exact same methods and procedures for participants in a research study
  • to control EVs
  • only the IV should vary
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15
Q

randomisation

A

-using chance (eg.flipping a coin) to control effects of a bias when designing a study

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16
Q

demand characteristics

A
  • characteristics of a study that may give away the purpose of the experiment
  • participants might become aware of aim
  • participants may change their behaviour to be seen in a better light/different way
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17
Q

experiments

A

looks at a measurable change in the DV caused by a change to the IV
(quantitative approach

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18
Q

lab experiment (type of experiment)

A
  • experimenter has a high control over what happens

- takes place in a laboratory

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19
Q

evaluate the use of lab experiments

A

strengths:
weaknesses:
-behaviour in a lab is less “normal”-difficult to generalise
-participants may change their behavior (they’re aware that they’re being watched)

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20
Q

field experiment (type of experiment)

A
  • takes place in a natural setting

- IV is manipulated by experimenter

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21
Q

evaluate the use of field experiments

A

strengths:
-more realistic than lab experiments (natural environment)
-can use standardised procedures (some control)
weaknesses:
-may lose control of EVs (difficult to show cause and effect)
-ethical issues (participants aren’t aware of the study

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22
Q

natural experiment (type of experiment)

A
  • takes place in a natural setting

- IV isn’t changed by experimenter (naturally occurring)

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23
Q

evaluate the use of natural experiments

A

strengths:
-high validity (due to the real world variables)
-can standardise procedures (some control over EVs)
weaknesses:
-few opportunities to do this kind of research as behaviours may be rare
-may be EVs (due to the fact that participants aren’t randomly allocated to conditions)

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24
Q

experimental designs

A

different ways participants can be organised in relation to IVs/conditions of the experiment

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25
Q

order effects

A

EV arising from the order in which conditions are presented (in repeated measures)

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26
Q

independent groups (experimental design)

A
  • different group of participants for each level of the IV (condition)
  • control and experimental group
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27
Q

evaluate the use of independent groups

A 
strengths:
order effects aren't a problem because participants only do the experiment once
weaknesses:
-different participants in each group
-participant variables can act as an EV
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28
Q

participant variable

A

differing individual characteristics of participants

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29
Q

how do you deal with participant variables?

A

allocation: using chance or a systematic method to allocate participants to conditions, this way the researcher doesn’t influence who goes in each group and also makes participant variables even across the different conditions

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30
Q

repeated measures (experimental design)

A

all participants take part in all levels of the IV

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31
Q

evaluate the use of repeated measures

A

strengths:
-no participant variables
-fewer participants needed so its less expensive
weakness:
order effects reduce validity (eg. practice effect: participants may do better the second time)

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32
Q

how do you deal with order effects?

A

counterbalancing: half the participants do the conditions in one order, other half do the opposite order

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33
Q

matched pairs

A
  • participants tested on variables relevant to the study

- participants are matched, and one member of each pair goes into each condition

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34
Q

evaluate the use of matched pairs

A 
strengths:
-no order effects
-fewer participant variables
weaknesses:
-takes time to match participants 
-doesn't control all participant variables
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35
Q

sample

A

subset of target population which aims to be representative of that population-aims to avoid bias

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36
Q

sampling method

A

system used to produce sample

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37
Q

target population

A

group that the researcher is interested in studying

purpose is to be able to generalise all findings/results to the target population

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38
Q

research bias

A

process where the scientists performing the research influence the results in order to to portray a certain outcome

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39
Q

random sampling

A
  • each person has equal chance of selection

- numbers of target population in hat/number generator

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40
Q

evaluate the use of random sampling

A

strengths:
-no bias (because everyone has an equal chance of selection)
weaknesses:
-takes time (have to make a list of members of the target population)

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41
Q

opportunity sampling

A

selecting people that are available

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42
Q

evaluate the use of opportunity sampling

A

strengths:
quick+cheap (participants are just there)
weaknesses:
only represents the population from which it was drawn

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43
Q

systematic sampling

A

selecting every nth person from a list of the target population

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44
Q

evaluate the use of systematic sampling

A

strengths:
avoids researcher bias
weaknesses:
may end up with unrepresentative

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45
Q

stratified sampling

A

selecting participants in proportion to frequency in target population

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46
Q

evaluate the use of stratified sampling

A

strengths:
very representative
weaknesses:
very time-consuming to sort sub-groups

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47
Q

what is the issue with psychological studies?

A

conflict between participants’ rights and well-being and the need to gain valuable results

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48
Q

informed consent

A

participants must be told comprehensive information (nature, purpose and role) at the beginning and they can make an informed decision about whether or not they want to take part (consent)

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49
Q

right to withdraw

A

they should be told that they can leave the investigation at any time they wish

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50
Q

deception

A

participants shouldn’t be lied to or misled about aim

—mild deception can be justified (withholding info about the other group/condition)

51
Q

privacy

A

participants have the right to control about themselves

52
Q

confidentiality

A
  • personal data must be protected and respected
  • data collected belongs to that person
  • personal details shouldn’t be accessible (usually anonymous)
53
Q

protection from harm

A
  • participants shouldn’t be placed at risk
  • physical and psychological safety should always be protected
  • not made to feel stressed or embarrassed
  • right to withdraw
54
Q

BPS guidelines

A

-code of conduct all professional psychologists in the UK need to follow

55
Q

how to deal with informed consent

A

participants (or guardians) sign a form that tells them what is to be expected

56
Q

how to deal with deception and protection from harm

A
  • participants have a full debrief to explain true aims and other conditions ect
  • participants are allowed to withhold data if unhappy with some aspects of study
  • reduce stress (assure them it was typical behaviour)
  • might be offered counseling)
57
Q

how to deal with privacy and confidentiality

A
  • participants must be anonymous (given numbers or referred to by initials)
  • data must not be shared unless given consent
  • participants should be reminded that data will be protected and remain confidential
58
Q

interviews

A
  • self report method

- face to face, real time contact and can also be done over phone or text

59
Q

structured interviews

A
  • reads list of questions
  • can have prepared follow up questions
  • follows exact script
60
Q

unstructured interviews

A
  • some questions prepared before
  • new questions created depending on what the interviewee says
  • much like a conversation
61
Q

semi-structured interviews

A
  • some questions decided before but follow up questions emerge at certain points
  • “goes with the flow”
62
Q

evaluate the use of interviews

A

strengths:
-produce a lot of info
-insight gained into thoughts and feelings
weaknesses:
-data can be difficult to analyse
-people may feel uncomfortable talking face to face

63
Q

questionnaires

A

prepared list of questions which can be answered in writing, over the phone, internet ect

64
Q

open questions

A
  • more likely in an interview
  • no fixed range of possible answers
  • respondents are free to reply in any way they wish
  • produces qualitative data
65
Q

closed questions

A
  • more likely in questionnaires
  • fixed range of possible answers
  • use rating scales, yes/no ect
  • produces quantitative data
66
Q

evaluate the use of questionnaires

A

strengths:
-can gather info from many people quickly
-questionnaires produce data that is easier to analyse than interviews (closed questions)-easier to make comparisons
weaknesses:
-social desirability bias (might not answer truthfully and give the answers they think is more appropriate/puts them in a better light—low validity
-may be unclear
-maybe be leading questions—lacks validity

67
Q

leading questions

A

a question that prompts or encourages the desired answer

68
Q

observation

A

a researcher watches or listens to participants and records data

69
Q

natural observation

A

researcher records behaviour where it would normally occur

70
Q

controlled observation

A

researcher manipulates aspects of the environment

71
Q

covert observation

A

participants aren’t aware behaviour is being recorded

72
Q

overt observation

A

told that they’re being recorded in advance

73
Q

participant observation

A

researcher is part of the group being recorded

74
Q

non-participant observation

A

researcher remains separate from the group that is being recorded

75
Q

categories of behaviour

A
  • systematic method of collecting data

- target behavior broken into separate observable changes

76
Q

interobserver reliability

A
  • observational studies should be carried out by more than one researcher because bias can be a problem
  • a single researcher may overlook important details or only record data that fits expectations
  • the group or pair should produce the same records of behavior
  • they would watch at the same time, have the same categories of behaviour and correlate data
77
Q

evaluate the use of observations

A

strengths:
-greater validity as it’s based of what people actually do (opposed to what they say they do which they could lie about)
-covert and natural observations show real life behaviour so it has high validity
weaknesses:
-ethical issues as researchers cant gain consent if they’re observing in a public place which invades their privacy
-observer bias:observers expectations affect validity as they may only record data that fits their expectations or may look over details

78
Q

correlations

A

shows how things are linked together (associations)

79
Q

co-variables

A
  • analysis of qualitative (numerical) data

- continuous data

80
Q

scatter diagrams

A
  • a special graph used to plot correlation data
  • one co-variable is on the x-axis and the other is on the y- axis
  • a dot is placed where they meet
81
Q

positive correlation

A

as one co-variable increases the other increases

82
Q

negative correlation

A

as one co-variable increases the other decreases

83
Q

zero correlation

A

no relationship between co-variables

84
Q

evaluate the use of correlations

A

strengths:
-allows psychologists to carry out investigations on things that cant be experimented on
-high level of ecological validity as nothing is set up or manipulated
weaknesses:
-don’t show cause and effect
-no control over EVs so wrong conclusions may be drawn

85
Q

case study

A

in-depth investigation of an individual, group, event or institution

86
Q

case studies:qualitative method

A
  • collect information about people’s experiences in words
  • data in a case study may be describing past events or interviews (qualitative)
  • some case studies may involve experimental testing that produces quantitative data (eg. intelligence tests which produce a numerical score) to see what the person can and cant do
87
Q

case studies:longitudinal

A
  • often carried out over a long period of time so we can see how behaviour changes
  • may also collect retrospective case history
88
Q

evaluate the use of case studies

A

strengths:
-triangulation:more than one method to collect data on the same topic
-naturally occurring
-high ecological validity
-rich and detailed qualitative data
weaknesses:
-lack of replication (every case is relatively unique)
-cant generalise findings (as it deals with only one person/group/event so you can never sure whether conclusions drawn from this case can be applied elsewhere)
-time consuming
-subjectivity bias causes low validity (findings are based on the psychologists opinion)

89
Q

reliability

A
  • if it can be repeated its reliable

- measure of consistency

90
Q

reliability of quantitative methods

A
  • tend to be more reliable
  • lab experiments are controlled and easy to repeat exactly
  • interviews/questionnaires: same person should answer the same questions in the same way- closed questions are likely to be more reliable
  • observations:one or two observers (interobserver reliability) should produce the same observations if repeated
91
Q

reliability of qualitative methods

A
  • less reliable

- case studies and unstructured interviews are difficult to repeat in the same way

92
Q

validity

A

relates to whether a result is a true reflection of “real world” behavior

93
Q

validity of sampling methods

A
  • the sample may not represent the target population
  • high representativeness=stratified
  • low representativeness=opportunity
94
Q

validity of experimental designs

A
  • repeated measures:order effects challenge validity (can be overcome by counterbalancing)
  • independent groups:participant variables challenge validity (can be overcome by random allocation)
  • matched pairs:overcome both problems (though it isn’t perfect)
95
Q

validity of quantitative methods

A
  • lab experiments: task, setting and participant awareness challenges validity=reduces naturalness and has high control
  • field experiments:artificial tasks and lack of control of extraneous variables challenge validity=more natural
  • methods for producing numerical data (eg questionnaires) lack validity as they reduce behavior to a score=therefore we get little to no insight into other aspects of their behavior
96
Q

validity of qualitative methods

A
  • case studies have greater validity as they give deeper insight into behavior, thoughts and the participant’s point of view
  • difficult to analyse=reduces validity, findings are fairly subjective and the researcher’s own expectations influence the analysis
97
Q

quantitative data

A
  • quantities (numbers)

- can measure thoughts/feelings

98
Q

evaluate the use of quantitative data

A 
strengths:
-easy to analyse an draw conclusions
-straightforward to make comparisons
-statistics are open to less interpretation=less chance of bias
weaknesses:
-lacks depth and detail
-lacks validity
-doesn't reflect real world complexity
99
Q

qualitative data

A
  • data in words

- can be turned into numbers by counting themes

100
Q

evaluate the use of qualitative data

A

strengths:
-more depth and detail
-better insight (participant is free to fully express thought)
-more validity
weaknesses:
-difficult to analyse and summarise (a lot of material)
-difficult to draw conclusions
-conclusions may be based on the researcher’s own opinions=open to bias

101
Q

primary data

A
  • data that has been obtained first hand

- collected data matches the aim of the study (collected for the purpose of the research)

102
Q

evaluate the use of primary data

A

strengths:
-suits the aims of the research=more useful
-authentic
weaknesses:
-takes time and effort to collect
-costly
-much easier and quicker to use that is already validated

103
Q

secondary data

A
  • second hand data
  • from other studies or government statistics
  • already exists
104
Q

evaluate the use of secondary data

A 
strengths:
-easy and convenient to use
-saves expenses
-saves time
-little effort
weaknesses:
-may not fit what the researcher is investigating 
-secondary data may be out-of-date, not quite complete or of poor quality=may waste time
105
Q

descriptive statistics

A

express numbers in a way that shows the overall pattern

106
Q

range

A
  • spread of data

- arranges data in order and subtracts the lowest from the highest score

107
Q

evaluate the use of ranges

A

strengths:
easy to calculate
weaknesses:
-can be distorted by extreme scores

108
Q

mean

A
  • mathematical average

- add up all the scores and divide by the number of scores

109
Q

evaluate the use of means

A

strengths:
-uses all the data (most sensitive measure)
weaknesses:
-can be distorted by extreme values

110
Q

median

A
  • data put in order from lowest to highest

- middle value

111
Q

evaluate the use of medians

A

strengths:
-not affected by extreme scores
weaknesses:
-less sensitive than the mean to variation in values

112
Q

mode

A

most common score

113
Q

evaluate the use of modes

A

strengths:
-very easy to calculate
weaknesses:
-can be unrepresentative

114
Q

frequency tables

A

-frequency: number or times it occurs-frequency tables are a systematic way to organize data in rows and columns

115
Q

frequency diagrams

A
  • histogram: continuous categories, no spaces between bars
  • bar chart: bars can be in any order
  • normal distribution: symmetrical spread forms a bell shape with mean, median and made at peak
116
Q

decimals

A
  • any number written with a decimal
  • position represents value
  • eg. 0.2
117
Q

fractions

A
  • reduce to simplest form

- eg. 1/2

118
Q

ratios

A
  • way to express fractions

- 8:2=4.1

119
Q

percentages

A
  • fractions out of 100

- eg. 58%

120
Q

finding the mean

A

add all scores and dividing by the number of scores

121
Q

standard form

A

mathematical shorthand to represent very large or very small numbers

122
Q

significant figures

A

numbers expressed to the required degree of accuracy eg.2 significant figure:

  • 32,462=32,00
  • 0.003256=0.0033
123
Q

estimate results

A

rough calculation

GCSE Psychology (AQA) 2024 (11 decks)

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