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Psychology > research methods > Flashcards

research methods Flashcards

1
Q

define aim

A

description of what you are researching and why

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2
Q

define hypothesis

A

states the relationship between the variables and predicts the results

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3
Q

define directional hypothesis

A

states the direction and correlation the experiment is expected to go in based on previous research

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4
Q

define non directional hypothesis

A

predicts there will be a difference in results but the direction is unknown as there is no previous research

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5
Q

define null hypothesis

A

predicts there will be no difference

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6
Q

define IV

A

variable we change

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7
Q

define DV

A

variable we measure

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8
Q

define operationalisation of variables and how to do it

A

clearly defining the variables and stating how they will be measured by adding values and units

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9
Q

define extraneous variables

A

variables other than IV that may have an effect on DV if not controlled and doesn’t relate to IV

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10
Q

define demand characteristics

A

clues that allow participant to guess the aim and changes their behaviour to help or sabotage the experiment

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11
Q

define social desirability

A

when the participant tries to please the researcher or try to make themselves look better

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12
Q

define the hawthorne effect

A

when people are interested so they show a more positive response which leads to artificially high results

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13
Q

define investigator/experimenter effects

A

experimenter unconsciously conveys to participant how they should behave

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14
Q

examples of investigator effects

A

tone, accent, body language, leading questions

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15
Q

define situational variables

A

aspects of environment that may affect the participants behaviour

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16
Q

examples of situational variables

A

temperature, noise, authenticity of experiment

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17
Q

define participant variables

A

the ways each participant varies and how this affects their results

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18
Q

examples of participant variables

A

trauma, mood, intelligence, anxiety, gender, culture

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19
Q

how can you control extraneous variables

A

single blind design
double blind design
experimental realism
randomisation
standardisation
controls

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20
Q

define single blind design

A

participant is not aware of the research aims

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21
Q

define double blind design

A

participant and experimenter are unaware of aim and hypothesis

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22
Q

define experimental realism

A

researcher makes the task engaging that the participant doesn’t know they are being observed

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23
Q

define randomisation

A

randomly allocating tasks and roles to avoid bias

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24
Q

define standardisation

A

experience of experiment is kept almost identical

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25
Q

define confounding variable

A

variable other than IV that had a direct effect on the DV and is related to IV

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26
Q

define pilot studies

A

small scale practice investigations to help identify potential problems before doing the real experiment, so money and time is saved and stops floor and ceiling effect

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27
Q

define validity

A

the extent to which a study measures what it intends to measure

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28
Q

define internal validity

A

whether the effects observed are due to the IV and not another factor

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29
Q

define mundane realism

A

how realistic the task is

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30
Q

define external validity

A

how well you can even compare your findings to other people, places and times

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31
Q

define ecological validity

A

the extent to which the results reflect real life

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32
Q

define population validity

A

how well the sample can be used to generalise to represent the population as a whole

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33
Q

define temporal validity

A

the extent to which the findings are valid when we consider differences in time progressions

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34
Q

how to assess validity

A

face validity and concurrent validity

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35
Q

define face validity

A

the test/questionnaire looks like it measures what it intends to

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36
Q

define concurrent validity

A

whether the results can be compared to another existing, well established test which measures the same thing and follows the same correlation

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37
Q

how to improve validity

A

control group- compare results with the experimental group to see if IV changes
covert observations- participant doesn’t know they are being watched so they are natural
questionnaires- keeping them anonymous so they are more truthful
qualitative methods- interviews have high ecological validity as they represent humans more accurately

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38
Q

define experimental design

A

researcher has to decide how they will use their participants

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39
Q

define a repeated measures experiment

A

same group if participants in all conditions

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40
Q

advantages of repeated measures experiment

A
  • no participant variables
  • fewer participants so more economical
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41
Q

disadvantages of repeated measures experiment

A
  • order effects
  • demand characteristics
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42
Q

define order effects and what are the different types

A

doing the same task twice
boredom, fatigue, practise

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43
Q

solutions to repeated measures experiment

A

counterbalancing and randomisation

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44
Q

define counterbalancing

A

when two groups do the tasks in different order to cancel our order effects

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45
Q

define independent group design

A

different groups perform only one condition

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46
Q

advantages of independent group design

A
  • no practice effects
  • reduces demand characteristics
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47
Q

disadvantages of independent group design

A
  • needs more participants
  • participant variables between groups
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48
Q

solutions to independent group design

A

random allocation as each participant had an equal chance to being in either group and tried to avoid imbalance of participant variables in either group

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49
Q

define matched pairs design

A

pair up participants on a certain quality that is believed to affect the performance on the DV and their results are compared

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50
Q

advantages of matched pairs design

A
  • participant variables reduced
  • no order effects
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51
Q

disadvantages of matched pairs design

A
  • larger number of participants needed
  • difficult to match on characteristics like personality
  • difficult to know which variables are relevant
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52
Q

solutions to matched pair design

A

pilot study to help choose which variables are most important to match on

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53
Q

define ceiling effect

A

task is too easy so all the scores are high

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54
Q

define floor effect

A

task is too difficult so all scores are low

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55
Q

define construct validity

A

extent to which a test captures a specific construct or trait and it overlaps with some other aspects of validity

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56
Q

define experiment

A

IV that is changed so that the effect on DV can be observed and aims to establish cause and effect relationship

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57
Q

define laboratory experiment

A

takes place in a carefully controlled lab where the IV is manipulated by the experimenter so the DV can be measured

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58
Q

pros of laboratory experiment

A
  • extraneous variables are closely controlled so increases internal validity
  • easily repeated as it is controlled so increases reliability
  • shows cause and effect relationship
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59
Q

cons of laboratory experiment

A
  • artificial nature so lacks ecological validity
  • know they are tested so may lead to demand characteristics
  • lacks mundane realism
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60
Q

define field experiment

A

conducted in natural setting where the IV is still manipulated so the DV can be measured

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61
Q

pros of field experiment

A
  • higher mundane realism
  • naturalistic so high ecological validity
  • demand characteristics are less likely
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62
Q

cons of field experiment

A
  • harder to control extraneous variables
  • ethical issues as the participant don’t know they are being studied
  • harder to replicate
  • IV may be operationalised in a way that lacks mundane realism
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63
Q

define natural experiment

A

IV naturally occurs, and would take place even without the research taking place, and DV is then measured

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64
Q

pros of natural experiment

A
  • high external validity
  • provides opportunities for research that would otherwise be impossible to replicate
  • reduced demand characteristics
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65
Q

cons of natural experiment

A
  • less control over extraneous variables
  • very unlikely to be able to replicate
  • random allocation of participant not possible so there may be bias and lead to participant variables
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66
Q

define quasi experiment

A

participants are automatically assigned to a condition depending on their characteristics or features that don’t change

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67
Q

pros of quasi experiment

A
  • controlled experiments so can be replicated
  • high ecological validity as you can compare to real life
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68
Q

cons of quasi experiment

A
  • cannot randomly allocate so more chance of extraneous variables
  • demand characteristics as they may become more aware
  • DV may be articulate and reduced ecological validity
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69
Q

define sampling

A

choosing a group of people to represent the target population

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70
Q

define target population

A

population to which the researcher would like to generalise their results to

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71
Q

define opportunity sample

A

using people who are available at the time of testing

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72
Q

define random sample

A

each member of the population has an equal chance of being selected like names in a hat or random generator

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73
Q

define stratified sample

A

subgroups are identified and participants are chosen at random from each group in proportion to target population

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74
Q

define volunteer sample

A

participants out themselves forward to take part

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75
Q

define systematic sample

A

using a system to pick a pattern of participants e.g every nth time

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76
Q

pros of opportunity sampling

A
  • quick and cheap
  • can have face to face ethical debriefings
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77
Q

cons of opportunity sampling

A
  • researcher bias as they bc hoods who they want
  • depends on who’s available, different factors eliminate who is free
78
Q

pros of random sampling

A
  • avoids bias
  • aims to be fair and representative
79
Q

cons of random sampling

A
  • impossible to have all names of target populayion
  • doesn’t guarantee full representation
  • time consuming
80
Q

pros of stratified sampling

A
  • highly representative so has population validity
81
Q

cons of stratified sampling

A
  • time consuming and difficult to gather
82
Q

pros of volunteer sampling

A
  • give their informed consent
  • will be interested and less likely to withdraw
  • large number may apply so it gives more accurate results and in depth analysis
  • helpful to find people who can be seen as atypical
83
Q

cons of volunteer sampling

A
  • biased as it is not representative of the whole population
  • hawthorne effect
  • demand characteristics
84
Q

pros of systematic sampling

A
  • normally representative
85
Q

cons systematic sampling

A
  • may not be able to identify all members of the population
  • unexpected bias that has a pattern
  • starting point and deciding on list type may be biased
86
Q

what are the ethical issues

A
  • informed consent
  • deception
  • right to withdraw
  • protection from harm
  • privacy and confidentiality
87
Q

features of informed consent

A
  • making participants aware of the aims of the research, procedures, risks, rights and what their data will be used for
  • use consent forms
  • under 16s need parental consent
  • consent cannot be given by those under the influence
88
Q

define presumptive consent

A

similar group of people are told the details of the study and asked if it is acceptable, and their answer will presume the answer of the actual participants

89
Q

define prior general consent

A

participants give their permission to be deceived but not knowing how

90
Q

define retrospective consent

A

asking them after they have taken part of their data can be used

91
Q

limitations of informed consent

A
  • invalidate purpose of study
  • participants do not know fully what they are getting in to
  • demand characteristics
92
Q

features of deception

A
  • BPS only allows when there is scientific justification and no alternative procedure
  • full debrief after to discuss concerns
  • cost-benefit analysis
93
Q

limitations of deception

A
  • cost- benefit decisions are flawed
  • debriefing cant turn back time
  • distrust in psychologists
94
Q

features of right to withdraw

A
  • enticed by financial incentives
  • fully informed consent so they know what they are doing and less likely to withdraw
  • volunteer samples as people are more eager and won’t withdraw
95
Q

limitations of right to withdraw

A
  • time consuming
  • guilty to withdraw
  • economic pressure because they are getting paid
96
Q

features of protection from harm

A
  • physical or psychological
  • should be in same state after the experiment as they were before
  • no greater harm than what they would experience in every day life
  • offer therapy and counselling at the end
  • stop the study immediately if the participant is harmed too much
97
Q

limitations of protection from harm

A
  • harm may not be apparent or obvious yet
  • don’t always know what will be harmful beforehand
98
Q

features of privacy and confidentiality

A
  • protected under data protection act
  • using code names and anonymity
  • deleting unnecessary daya
99
Q

limitations of privacy and confidentiality

A

still work out participants from limited amount of information

100
Q

define naturalistic observation

A

behaviour in natural situation or environment without any intervention

101
Q

advantage of naturalistic observation

A

high external and ecological validity

102
Q

disadvantages of naturalistic observation

A
  • less control over extraneous variables
  • replication is difficult
103
Q

define controlled observations

A

some variables are controlled by the researcher and participants are likely aware that they are being studied

104
Q

advantages of controlled observation

A
  • more control over extraneous variables
  • easy replication
105
Q

disadvantage of controlled observation

A
  • low ecological validity and mundane realism
  • demand characteristics
106
Q

define overt observation

A

participants are aware they are being observed, but observers may try to be as unobtrusive as possible

107
Q

advantages of overt observation

A

infrom participants and ask for consent

108
Q

disadvantage of overt observation

A
  • demand characteristics
  • social desirability bias
109
Q

define covert observation

A

participants are unaware they are being observed

110
Q

advantages of covert observation

A
  • higher ecological validity
  • natural behaviour so high internal validity
111
Q

disadvantages of covert observation

A

ethical concerns because they cannot give consent

112
Q

define non participant observation

A

observer is merely watching or listening to the behaviour of others and not interacting with

113
Q

advantage of non participant observation

A

observer effects less likely

114
Q

disadvantage of non participant observation

A

less insightful

115
Q

define participant observation

A

observer is part of the group being observed

116
Q

advantage of participant observation

A

more insightful

117
Q

disadvantage of participant observation

A
  • demand characteristics
  • lose objectivity
118
Q

advantages of observations

A
  • high validity
  • captures spontaneous and unexpected behaviour
119
Q

disadvantages of observation

A

-observer bias
- only observable behaviour can be recorded
- hard to replicate

120
Q

define inter-observer reliability

A

if several observers are coding behaviours, their codings agree with each other

121
Q

features of inter observer reliability

A
  • should agree beforehand the behavioural categories and their interpretations of them
  • carry observations at the same time but in different places
  • total number of agreements / number of observations
122
Q

define unstructured observation

A

all relevant behaviours is recorded and no system is used

123
Q

evaluation of unstructured observation

A

+ greater insight
- observer bias, unnecessary behaviours noted (time wasting)

124
Q

define event sampling

A

counting the number of times a certain behaviours occurs

125
Q

evaluate event sampling

A

+ focuses on an event, find averages
- cant note abnormal behaviours, no indication of when it happened

126
Q

define time sampling

A

recording behaviour at preset intervals of time

127
Q

evaluate time sampling

A

+ frequencies within observation, more objective
- may miss something, demand characteristics, observer bias, social desirability bias

128
Q

define structured observations

A

use various systems to record behaviour

129
Q

evaluate structured observations

A

+ smaller risk of observer bias
- less insight as they are nothing frequencies of behaviour, interesting behaviours unwritten

130
Q

define behavioural categories and criteria of them

A

target behaviour is operationalised so it’s more reliable and measurable
- objective- no inferences have to be made
- cover all possible behaviours and no waste basket
- criteria shouldn’t overlap

131
Q

define self report techniques and why they are useful

A

participants give information about themselves, including their experiences, beliefs and feelings

132
Q

types of closed questions

A

likert scale- indicated agreement from strongly agree to strongly disagree
ranked scale- from 1 to 10
semantic differential scale- indicate where they fall between two extremes
multiple choice- choose from
options

133
Q

advantages of closed auestions

A

easy to analyse

134
Q

disadvantages of closed questions

A
  • forced to pick an option that doesnt represent them
  • waste baskets
135
Q

advantages of open questions

A
  • more detail and can expand on answers
  • allow for unexpected answers
136
Q

disadvantages of open questions

A
  • worry of confidentiality
  • qualitative data not produced
137
Q

advantages of questionnaires

A
  • can be distributed to large numbers cheaply and quickly
  • may be more willing to participate
138
Q

disadvantages of questionnaires

A
  • not accessible to all (literate)
  • social desirability bias
  • leading questions so response bias
  • takes a long time to design
  • participant bias
  • sample not representative
  • acquiescence bias (tendency to agree with things)
139
Q

criteria for questionnaire design

A
  • easily analysed so more likely closer questions
  • free from bias and leading questions
  • should be clear and avoid using double negatives
  • make language understandable for all
  • contain filler questions to reduce demand characteristics
  • sequence questions sensibly
  • avoid double barrelled questions with more than one answer
  • pilot study
140
Q

define correlation

A

relationship and strength between two variables

141
Q

define positive correlation

A

as one co-variables increases, the other increases too

142
Q

define negative correlation

A

as one co-variable increases, the other decreases

143
Q

define no correlation

A

no relationship between the two variables

144
Q

define intervening variables

A

another variables that had not been studied

145
Q

define continuous variable

A

variable that can take on any value within a certain range and not categorised

146
Q

explain correlation coefficients

A
  • between -1 and +1
  • show strength of the co-variables
  • coefficients above 0.8 have a strong correlation and are reliable and valid
147
Q

define quantitative data

A

data in the form of numbers

148
Q

strengths of quantative data

A
  • reliable
  • can be analysed statistically
  • easy to compare and analyse
149
Q

weaknesses of quantitative data

A
  • lacks detail
  • may oversimplify
150
Q

define qualitative data

A

data in the form of words

151
Q

strengths of qualitative data

A

-detailed

152
Q

weaknesses of qualitative data

A
  • subjective
  • unreliable
  • hard to compare
  • time consuming
  • researcher bias
153
Q

define triangulation

A

use of a mixture of qualitative and quantitative data

154
Q

define primary data

A

information observer and collected directly from first hand experience, including designing and carrying out the study

155
Q

strengths of primary data

A
  • more reliable
  • can cater to your research
156
Q

weaknesses of primary data

A
  • time consuming and costly
  • many not have access to groups and data you need
  • ethical considerations
157
Q

define secondary data

A

information that was collected from other studies

158
Q

benefits of secondary data

A
  • use data from bigger samples
  • access to information you wouldn’t be able to reach
  • meta- analysis
  • quicker
  • objective and detached
159
Q

weaknesses of secondary data

A
  • may not be exactly what you are researching
  • may not understand research in detail
  • takes time to analyse
  • outdated
  • unreliable
160
Q

define meta analysis

A

analyse results from loads of different studies and come up with general conclusions

161
Q

benefits of meta analysis

A
  • help to identify trends
  • increase sample size and reliability of findings
162
Q

weaknesses of meta analysis

A
  • publication bias like file drawer problem where researcher intentionally does not publish all the data
  • some research may contradict each other
163
Q

what are the measures of central tendency and how do you work them out

A

mean- add all number together and divide by how many values there are
median- putting the numbers in order and finding the middle number
mode- most common number

164
Q

evaluation of mean

A

+considers all data, used for further calculations
- can be skewed by extreme values and make it unrepresentative, can give unrealistically precise values that don’t work for discrete data

165
Q

evaluation of median

A

+ will not be affected by extreme values
- may not be representative, little further use

166
Q

evaluation of mode

A

+ will not be affected by extreme values, makes more sense when presenting discrete values, easy to use
- does not use all data, may have more than one mode, little further use

167
Q

what are the dispersion techniques and how to work them out

A

range- highest minus lowest
standard deviation- spread around the mean

168
Q

evaluation of range

A

+ can see consistency, easy to calculate
- affected by extreme values, fails to account distraction, does not account numbers in the middle

169
Q

evaluation of standard deviation

A

+ precise measure where all values are taken into account
- difficult to calculate, affected by extreme values

170
Q

define longitudinal studies

A

studies conducted over a long period of time to observe long term effects between the same individual

171
Q

evaluation of longitudinal studies

A

+ in depth, reduces participant variables
- extraneous variables, people might drop out

172
Q

define cross sectional studies

A

group of participants are compared to another group at the same point in time

173
Q

evaluation of cross sectional studies

A

+ efficient, more control over experiment
- participant variables

174
Q

define cross cultural studies

A

compare behaviours in different cultures

175
Q

how to display quantitive data

A
  • table
  • line graph
  • histogram
  • bar chart
  • scattergram
  • pie chart
176
Q

features of tables

A
  • clearly present data and show any patterns
  • raw data to show scored before analysis
177
Q

features of line graphs

A
  • can show more than one set of data
  • continuous data in list form
  • independent on x and dependent on y
  • join each point up
  • see trends over time
178
Q

features of histograms

A
  • continuous scale
  • uses class intervals
  • columns touch each other
  • frequencies of scores
179
Q

features of bar charts

A
  • non- continuous data
  • columns do not touch
180
Q

features of scattergrams

A
  • show relationship and correlation between two variables
  • continuous data on both axis
  • draw line of best fit
181
Q

features of pie chart

A
  • sectors of a circle to show proportion
182
Q

define content analysis

A

quantifying qualitative data through the use of coding units

183
Q

features of content analysis

A

-indirect form of observation as you analyse artefact people have produced
- put into categories or typologies, quotations and summaries

184
Q

what sampling method in content analysis

A

analysing content every n number of times

185
Q

how to carry out coding in content analysis

A
  1. watch/read the sample and identify potential categories which have emerged
  2. compare categories/ coding unit with another psychologist and use the ones they have agreed upon
  3. give examples of the categories that they would be looking for and operationalise
  4. carry out content analysis separately and counting the number of examples that fall into each category
  5. compare examples to look for agreement
186
Q

define thematic analysis

A

recurring themes identified during coding and are described further in greater detail, perhaps by conducting further analysis

187
Q

define test-retest reliability

A

conduct the content analysis and then recode them at a later date and compare the two sets of data

188
Q

evaluation of content analysis

A

+ easy to perform, non-invasive and ethical, high ecological validity, easily repeated and reliable
- observer bias, subjective, non-descriptive, cultural bias, may not have ecological validity compared to real life, choice of content can be biased

189
Q

define case study

A

in depth investigations of a single person, group of people or event

190
Q

features of a case study

A
  • represents thoughts, emotions, experiences and abilities
  • longitudinal- follow over an extended period of time
  • qualitative data like interviews, observations and questionnaires
  • examples like HM and KF
191
Q

evaluation of case studies

A

+ rich detail, help construct theories, help study the unusual
- hard to generalise, ethical issues like confidentiality and psychological harm, objectivity, past records may be biased or incomplete, hard to establish cause and effect

Psychology (7 decks)

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