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Psychology > Research Methods: Strengths + Weaknesses > Flashcards

Research Methods: Strengths + Weaknesses Flashcards

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1
Q

Strengths of Repeated Measures Design

A

individual differences are removed compared to individual groups

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2
Q

Weaknesses of Repeated Measures Design + how to deal with them

A
  • order effects: order of conditions could affect performance: short break, two different tests, counter balancing: ensures each condition is tested first or second in equal amounts
  • demand characteristics: ps guess aim of study and alter behaviour: single blind study: ps dont know true aim
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3
Q

Strengths of Independent Group Design

A

no order effects

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4
Q

Weaknesses of Independent Groups Design + how to deal with them

A
  • no control of ps variables
  • need twice as many ps
  • randomly allocate ps to conditions to ensure theyre equivalent
  • match ps
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5
Q

Strengths of Matched Pairs Design

A
  • controls some p variables
  • ps wont guess aim
  • no order effects
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6
Q

Weaknesses of Matched Pairs Design + how to deal with them

A
  • difficult and time consuming
  • may be too costly
  • may not control all variables
  • restrict number of varibales to be matched on
  • pilot study could show key variables that need to be matched
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7
Q

Strengths of Random Sampling

A

unbiased: all members of target population have equal chance of being selected

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8
Q

Weaknesses of Random Sampling

A

need to have a list of everyone in population and then contact those selected: takes time

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9
Q

Strengths of Opportunity Sampling

A
  • easiest method
  • reduces costs and time taken to find ps
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10
Q

Weaknesses of Opportunity Sampling

A

drawing sample from such a small part of population will prodcue bias

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11
Q

Strengths of Stratified Sampling

A

most representative of all methods as sample is proportionate to subgroups and random

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12
Q

Weaknesses of Stratified Sampling

A

very time consuming to identify subgroups and randomly select ps and then contact them

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13
Q

Strengths of Systematic Sampling

A

unbiased as ps are selected using an objective system

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14
Q

Weaknesses of Systematic Sampling

A

not truly unbiased/random unless you start with a random method for selecting the first ps and then select every nth person

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15
Q

Strengths of Volunteer Sampling

A

wide variety of people which may make sample more representative

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16
Q

Weaknesses of Volunteer Sampling

A

sample may be biased towards people who are motivated/confident or need money resluting in a volunteer bias

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17
Q

Strengths of Lab Experiment

A
  • easy to replicate: increases external validity
  • good control over IV and DV: less extraneous variables
  • easy to establish cause + effect
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18
Q

Weaknesses of Lab Experiment

A
  • materials may lack mundane realism
  • researchers cant be sure they are behaving naturally as there may be demand charcateristics
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19
Q

Strengths of Field Experiment

A
  • higher mundane realism
  • ps dont know they are being studied so no demand charcteristics
  • real world study so more ecological validity and mundane realism
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20
Q

Weaknesses of Field Experiment

A
  • may be time consuming and unpredictable
  • less control over extraneous variables so hard to establish cause + effect
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21
Q

Strengths of Natural Experiment

A
  • ps dont know they are being studied so no demand characteristics
  • great for research that may be unethical to conduct
  • its a real world study so more ecological validity and mundane realism
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22
Q

Weaknesses of Natural Experiment

A
  • random allocation not possible, therefore there may be confounding variables that can threaten internal validity
  • as we are not manipulating the IV it makes it hard to establish cause + effect
  • less control over extraneous variables so hard to establish cause + effect
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23
Q

Strengths of Quasi Experiment

A
  • allows comparison between types of people
  • good control over IV and DV, so less extraneous variables
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24
Q

Weaknesses of Quasi Experiment

A
  • random allocation not possible, therefore there may be confounding variables that can theaten internal validity
  • low in ecological validity
  • researchers cant be sure they are behaving naturally as there may be demand charcteristics
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25
Q

Strengths of Controlled Observations

A
  • less risk of extraneous variables: increases ability to interpret findings
  • richer and more complete info is obtained
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26
Q

Weaknesses of Controlled Observation

A
  • artificial situations can influence behaviour
  • artificially makes it hard to generalise findings: lacks ecological validity
  • investigator effects + demand characteristics from ps knowing theyre being observed
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27
Q

Strengths of Naturalistic Observations

A
  • removes problems from demand characteristics or evaluation apprehension
  • provide richer + fuller info
  • ecological validity
  • may work better with children and animals
28
Q

Weaknesses of Naturalistic Observations

A
  • no control: extraneous variables
  • often aware of observation
  • problems of replication
  • ethical issues if ps dont know behaviour is being observed
29
Q

Strengths of Covert Observations

A
  • reduces risk of altering behaviour: valid
30
Q

Weaknesses of Covert Observations

A
  • ethical problem of deceit
  • doesnt allow observer to ask more qs
  • observer cant take notes openly
31
Q

Strengths of Overt Observations

A
  • avoids ethical problem
  • can ask more qs
  • can take notes openly
  • can use interview methods to check insights
32
Q

Weaknesses of Overt Observations

A
  • group may refuse researcher permission to observe: may prevent them from seeing everything
  • hawthorne effect: behave differently, undermines validity
33
Q

Strengths of Participant Observations

A
  • high in ecological validity: real life settings
  • long lasting: detailed + rich info
  • in some its difficult for useful research to be carried out if havent joined group
  • easy to interpret ps behaviour as developed deep understanding
34
Q

Weaknesses of Participant Observations

A
  • ethical problems: deceiving
  • could change + distort behaviour of group members: investigator effects
  • issues of accuracy + objectivity: write after, become involved: bias
35
Q

Strengths of Non Participant Observations

A
  • high ecological validity under naturalistic
  • avoids investigator effects
  • observations less distorted as researcher is detached
36
Q

Weaknesses of Non Participant Observations

A
  • harder to make detailed observations
  • detachment makes it difficult to interpret behaviour
  • ps may become suspicious
37
Q

Strengths of Questionnaires

A
  • cost effective: large amount of data collected quickly
  • researcher doesnt need to be present
  • may be willing to share more info
38
Q

Weaknesses of Questionnaires

A
  • social desirability bias: respondents may not be truthful: loss of validity
  • can take a long time to design
  • only a certain type may respond
  • interpret qs in different ways
  • cant clarify qs
39
Q

Strengths of Unstructured Interviews

A
  • more flexibility than a structured interview as interviewer can follow up points as they arise: richness of data increases validity
  • easier to develop rapport
40
Q

Weaknesses of Unstructed Interviews

A
  • training needed
  • analysis of results/data not simple and due to there being potentially so much info its hard to draw conclusions
  • may be an element of social desirability bias
41
Q

Strengths of Structured Interviews

A
  • straightforward to replicate due to standardised format
  • reduces differences between interviewers
  • easy to compare
  • fairly quick
42
Q

Weaknesses of Structured Interviews

A
  • not possible for interviewers to deviate off topic or explore interesting points
  • stops interviewees from being able to elaborate which can be frustrating
  • limits richness of data: can decrease validity
43
Q

Strengths of Primary Data

A
  • control the researcher has over data
  • clearly fits aims and hypothesis of study
44
Q

Weaknesses of Primary Data

A
  • very lengthy and therefore expensive process: recruiting participants, conducting study, analysing data
45
Q

Strengths of Secondary Data

A
  • simpler and cheaper
  • plays important role in psychological research including review studies, meta analyses and correlational studies
46
Q

Weaknesses of Secondary Data

A
  • variation in quality + accuracy of data: could be outdates or incomplete
  • may not exactly match the researchers requirements
47
Q

Strengths of Correlations

A
  • can allow us to study naturally occuring variables
  • can measure things we cant experimentally due to ethical issues
  • can suggest patterns that then lead to experiments
48
Q

Weaknesses of Correlations

A
  • can tell us how variables are related but not why
  • correlation doesnt equal causation (there is no cause and effect relationship as its not experimental)
  • may overlook an important intervening variable
  • bidirectional ambiguity: unclear which direction correlation is going in
49
Q

Strengths of Mean

A
  • it takes all scores into account so its the most sensitive measure
50
Q

Weaknesses of Mean

A
  • can give a peculiar measure that cannot represent reality
  • easily distorted by extreme scores making it unrepresentative
51
Q

Strengths of Median

A
  • unaffected by extreme scores in one direction
  • more representative than the mean, especially with small data sets
52
Q

Weaknesses of Median

A
  • less representative when the data set is polarised
53
Q

Strengths of Mode

A
  • most useful for large data sets
  • unaffected by extreme scores
54
Q

Weaknesses of Mode

A
  • unreliable for use with small data sets as small changes to the scores can result in it being multi-modal
55
Q

Strengths of Range

A
  • useful when median is being used as an average as the range used the top and middle set and median is the middle number
  • easy to calculate
56
Q

Weaknesses of Range

A
  • easily distorted by extreme scores
  • only uses 2 numbers no matter how large data set is so its a really basic indication of how data is spread
  • doesnt give an indication of spread of data scpres as it just looks at highest and lowest scores
57
Q

Strengths of Standard Deviation

A
  • uses all scores in data set for calculation so its a more precise measure of the spread of data
58
Q

Weaknesses of Standard Deviation

A
  • more difficult to calculate than range
  • may hide some extreme scores within data set
59
Q

Strengths of Case Studies

A
  • gives very rich detailed info about the case
  • can be used to investigate rare behaviours
  • can be used to investigate behaviours that would be unethical to manipulate
  • converging evidence: increases validity
60
Q

Weaknesses of Case Studies

A
  • each case unique so not generalisable
  • may have to recall past (retrospective recall) which could be distorted
  • researcher bias could be an issue if they are looking for a particular thing
61
Q

Strengths of Peer Review

A
  • peers should be experts in the field so we know that we can trust their judgement
  • journals are international which means that there will be widespread dissemination of the new research among peers
  • published research provides benefits for the unis the researchers work for
  • peer review ensures that only the best research gets published
  • anonymity allows peers to be honest
  • publication in peer reviewed journals can enhance the reputation of researchers
62
Q

Weaknesses of Peer Review

A
  • it isnt always possible to find an appropriate expert to review a research proposal or report
  • peer review results in a preference for research that goes with existing theory rather than dissenting or uncoventional research
  • academic journals are expensive to buy
  • anonymity may mean peers abuse their position
  • journals may only want to publish positive results to increase the standing of the journal
63
Q

Strengths of Content Analyses

A
  • high ecological validity: content is part of evryday, not artificial
  • replicable: anyone can access same media and apply same behavioural categories
  • few ethical issues: isn’t any people in them as you’re observing the media
64
Q

Weaknesses of Content Analyses

A
  • investigator bias: bring own prejudices and preconceptions very easily especially when defining operationalised codes
  • culture bias: content tends to come from one culture, isn’t representative
65
Q

Strengths of Thematic Analyses

A
  • flexibility: only notice themes as they emerge
  • allows researchers own perspective: subjective nature
  • few ethical issues: isn’t any people in them
66
Q

Weaknesses of Thematic Analyses

A
  • can’t use statistics: generates qualitative data
  • subjectivity: may not spot themes they don’t personally relate to
67
Q
A

Psychology (25 decks)

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