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research methods Flashcards

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1
Q

types of sampling

A
  • opportunity
  • volunteer
  • random
  • systematic
  • stratified
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2
Q

sampling
OPPORTUNITY

A
  • most available / easiest to obtain

✔ quick + convenient method

✘ unrepresentative sample
- so cannot be generalised

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3
Q

sampling
VOLUNTEER

A
  • self-selecting

✔ willing ppts
- likely to engage more

✘ volunteer bias
- ppts may share certain traits
- limited generalisation

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4
Q

sampling
RANDOM

A
  • every person in target population has an equal chance of being selected

✔ unbiased
- researcher has no influence over who is selected
- free from researcher bias

✘ people selected may be unwilling to take part

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5
Q

sampling
SYSTEMATIC

A
  • ppts selected using a sampling frame
  • every nth person

✔ unbiased
- first item is usually selected at random
- free from researcher bias

✘ requires time + effort
- requires complete list of population
- random sampling would be more ideal

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6
Q

sampling
STRATIFIED

A
  • strata within the population is identified (eg age, gender)
  • sample reflects proportion of different strata

✔ representative
- characteristics of target population are represented
- allows generalisation

✘ imperfect
- strata can’t reflect all the ways in which people are different

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7
Q

research issues

A
  • extraneous variables: nuisance variables
  • confounding variables: change systematically w IV so can’t be sure if any observed change in DV is due to IV or CV
  • demand characteristics: any cue that may reveal aim of study
  • investigator effects: any effect of investigator’s behaviour on outcome of study
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8
Q

research techniques

A
  • randomisation: use of chance to control effect of bias
  • standardisation: same formalised procedure for all ppts - more repeatable
  • control groups: to set a comparison
  • single bind: ppt doesn’t know aim of study (to reduce demand characteristics)
  • double bind: both ppt + researcher don’t know aims of study (reduces demand characteristics + investigator effect)
  • counterbalancing: half of ppts in sample carries out conditions in 1 order + the other half in reverse order - eliminates order effect w repeated measures design
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9
Q

pilot studies

A

small-scale trial run of a study before doing the real thing to see if there’s any problems with:
- experimental design
- intructions for ppts
- measuring instruments

  • to ensure time, effort + money aren’t wasted on a flawed methodology
  • important to use a representative sample of target population
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10
Q

experimental methods
LAB

A
  • controlled environment where extraneous variables can be regulated
  • IV is manipulated + effect on DV is recorded

✔ high degree of control
- minimises effect of extraneous variables
- conclusions about cause + effect can be drawn confidently
- high internal validity

✔ standardised procedure
- can be easily replicated - can confirm validity

✘ lacks external validity
- limits generalisability

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11
Q

experimental method
FIELD

A
  • natural setting
  • IV manipulated + effect on DV recorded

✔ high ecological validity
- representative of behaviour in everyday life
- results are more generalisable

✔ ppts unaware they’re being studied
- no demand characteristics
- high internal validity

✘ less control over extraneuos variables
- more difficult to draw conclusions about cause + effect
- low internal validity

✘ ethical issues
- no informed consent
- invasion of privacy

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12
Q

experimental method
NATURAL

A
  • IV not manipulated
  • measures effects of existing IV (naturally occurring, eg flood/earthquake) on the DV

✔ greater ecological validity
- involve real-life issues
- findings are more relevant to real experiences

✘ natural event may only occur rarely
- reduces opportunity for research
- limits scope for generalisation

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13
Q

experimental method
QUASI

A
  • IV based on pre-existing difference between people, e.g. age or gender
  • measures effect of this IV on DV

✔ high control
- high internal validity

✔ comparisons can be made between people

✘ ppts are not randomly allocated

✘ causal relationships not demonstrated

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14
Q

experimental design
INDEPENDENT GROUPS

A
  • ppts randomly allocated to different groups
  • 1 does condition A; other does condition B

✔ no order effects
✔ reduces demand characteristics
✘ participant variables - may reduce validity
✘ more participants required - time-consuming

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15
Q

experimental design
REPEATED MEASURES

A
  • same ppts take part in all conditions
  • order of conditions should be counterbalanced to avoid order effects

✔ controls participant variables
✔ fewer participants
✘ order effects
✘ increases demand characteristics

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16
Q

experimental design
MATCHED PAIRS

A
  • 2 groups of ppts used but are paired on participant variables that matter for the experiment

✔ controls participant variables + demand characteristics
✔ no order effects
✘ matching is time consuming and can’t control all relevant variables
✘ more participants required - time consuming

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17
Q

observational techniques
naturalistic vs controlled

A

naturalistic: takes place where target behaviour would normally occur
✔ high ecological validity
- more generalisable
✘ low control
- low internal validity

controlled: some manipulation of variables including control of EVs
✔ replicable
-standardised procedures
✘ low external validity
-limits generalisation

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18
Q

observational techniques
covert vs overt

A

covert: ppts unaware they’re being studied
✔ eliminates demand characteristics
- high external validity
✘ ethically questionable
- ppts right to privacy

overt: ppts are aware they’re being studied
✔ more ethically acceptable
- ppts have given consent
✘ demand characteristics
- may influence behaviour
- lower external validity

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19
Q

observational techniques
participant vs non-participant

A

participant: when researcher becomes part of the group they are studying
✔ greater insight
- enhances validity of findings
✘ less objective
- more bias

non-participant: when researcher remains separate from group they are studying
✔ more objective
- less chance of bias
✘ loss of insight
- may reduce validity of findings

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20
Q

observational methods

A

behavioural categories: target behaviour to be observed broken up into set of observable/measurable categories
✘ difficult to make clear + unambiguous
- have to be self-evident + must not overlap

time sampling: target behaviour is recorded at prescribed intervals
✔ reduces no. of observations
- more structured + systematic
✘ may be unrepresentative
- may not reflect the entire behaviour

event sampling: target behaviour is recorded every time it occurs
✔ may record infrequent behaviour which could be easily missed during time sampling
✘ complex behaviour oversimplified
- may affect validity of findings

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21
Q

self-report techniques
QUESTIONNAIRES

A
  • made up of a pre-set list of written questions to which a ppt responds

✔ can be distributed to a lot of people
- large amounts of data gathered quickly
- cost-effective
✔ respondents may be willing to open up
- less chance of social desirability bias
✘ may not be honest
✘ acquiescence bias (response bias)
- tendency to agree regardless of their beliefs
- or not reading the question properly

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22
Q

questionnaires
open vs close

A

closed questions: respondent has limited choices
+ data is quantitative
✔ easier to analyse + draw conclusions
✘ respondents are restricted
- may be unrepresentative
- reduces validity of findings

open questions: respondents provide own answers expressed in words + data are qualitative
✔ not restricted
- more detailed answers
- more insightful
✘ difficult to analyse

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23
Q

self-report techniques
INTERVIEWS

A

interview schedule
standardised list of qs for interviewer to cover
can reduce interviewer bias
quiet room
will increase likelihood of ppt opening up
rapport
beginning w neutral qs to make ppt feel relaxed
ethics
remind ppts that answers will be treated in confidence

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24
Q

interviews
structured vs unstructured

A

structured: list of pre-determined qs asked in a fixed order
✔ easy to replicate
- standardised format
✘ interviewees cannot elaborate / deviate from topic

unstructured: general topic to be discussed, free-flowing interaction
✔ greater flexibility
- more likely to gain insight
✘ difficult to replicate
- risk of interviewer bias
- semi-structred

25
Q

correlations

A
26
Q

case studies

A
  • detailed, in-depth + longitudinal analysis of an individual/group/institution/event
  • often involves analysis of unusual individuals or events
  • eg person w rare disorder
  • usually involves qualitative data

✔ rich, detailed insight
- increases validity of data
✔ enables study of unusual behaviour
- some conditions are very rare + cannot we studied using other methods
- some cases can help understanding of normal functioning
✘ low ecological validity
- studying a single person/event
- unique cases
- difficult to generalise to wider population
✘ prone to researcher bias
- based on the subjective interpretation of the researcher
- may reduce validity
✘ ppts accounts may be biased
- personal accounts prone to inaccuracy/memory decay
- evidence may be low in validity.

27
Q

ethical issues
INFORMED CONSENT

A

ppts should be aware of aims of research, procedures, their rights (incl to withdraw) + what their data will be used for in order no make an informed decision about whether to take part

dealing w it:

  • should be issued w a consent letter, detailing all relevant info that may affect their decision to participate + a signature must be obtained
28
Q

ethical issues
PROTECTION FROM HARM

A

ppts should leave research in the same psychological + physical state as they entered; should be at no more risk than they would in everyday life

dealing w it:

  • should be reminded of their right to withdraw at each stage of the research process
  • should be debriefed at the end + reassured that their behaviour was normal
  • may be referred to counselling in some cases
29
Q

ethical issues
DECEPTION

A

deliberately misleading or witholding info from ppts meaning consent is not informed

dealing w it:

  • at the end of the study, ppts should be given a full debrief, including the true aims + nature of the research what their data will be used for
  • should be given the right to withold data if they wish
  • should also be reassured that their behaviour was normal
  • in extreme cases, they may be offered counselling
  • contact details of experimenter should be given if they have any further questions of queries
30
Q

ethical issues
CONFIDENTIALITY

A

a ppt’s personal info is protected by law under the Data Protection Act both during + after the experiment

dealing w it:

  • any personal info should remain undisclosed to protect their identity + assure anonymity
31
Q

ethical issues
PRIVACY

A

the right of individuals to decide how info about them will be communicated to others

dealing w it:

  • should be provided w informed consent + right to withdraw at any stage
  • should be explained the ways in which their info will be protected + kept confidential
32
Q

peer review

A
  • before publication, all aspects of the investigation are scrutinised by experts (peers) in the field
  • these peers should be objective + unknown to the researcher

aims to:
* funding - allocate research funding
* validation of the quality + relevance of research
* improvements + ammendments are suggested
*

33
Q

economical implications

A
34
Q

types of data
quantitative vs qualitative

A

quantitative: numerical data
✔ easier to analyse + draw conclusions
- more objective + less open to bias
✘ oversimplifies behaviour
- doesn’t provide meaningful insight

qualitative: non-numerical data expressed in words
✔ more detailed
- thoughts + feelings can be explained
✘ difficult to analyse + draw conclusions

35
Q

types of data
primary vs secondary

A

primary: firsthand data collected for purpose of investigation
✔ info is directly relevant to research aims
✘ requires time + effort

secondary: taken from journal articles, books, websites or gov records
✔ already exists
- inexpensive + minimal effort
✘ quality may be poor
- may be outdated/incomplete
- challenges validity

36
Q

types of data
meta-analysis

A
  • type of secondary data that involves combining data from a large no. of studies

✔ increases validity of conclusions
- much larger sample size
- more generalisable
✘ publication bias
- may not select all relevant studies

37
Q

descriptive statistics
measures of central tendency

A

mean: arithmetic average
✔ sensitive
- includes all values from data set in calculation
✘ may be unrepresentative
- easily distorted by any extreme values

median: middle value
✔ unaffected by extreme values
- only focussed on middle value
✘ less sensitive than mean
- not all values included in calculation
- extreme values may be important

mode: most frequently occurring value
✔ relevant ro discrete/categorical data
- sometimes the only appropriate measure
✘ overly simple
- may be many modes in a data set
- not useful in this case

38
Q

descriptive statistics
measures of dispersion

A

range: difference between the highest + lowest values
✔ easy to calculate
✘ only takes into account 2 most extreme values
- unrepresentative of data set as a whole
- doesn’t account for distribution of values

standard deviation: measure of average spread around the mean
✔ more precise than range
- includes all values in calculation
✘ may be misleading
- extreme values may not be revealed

39
Q

presentation + display of quantitative data

A
40
Q

distributions

A
41
Q

content analysis

A

type of observational research where people are studied indirectly via qualitative data (their communications, eg texts, emails, TV, film and other media)

coding: 1st stage of content analysis
- data sets may be extremely large so info needs to be categorised into units eg counting up no of times a word/phrase appears in a text
- produces quantitative data

thematic analysis: produces qualitative data + refers to any idea that is recurrent
- more descriptive than coding units

✔ many ethical issues may not apply
eg obtaining consent
- as material already in public domain
✔ flexible method
- can be adapted to suit aims of the research
✘ communication is studied out of context
- likely to reduce validity

42
Q

reliability

A
  • measure of consistency
  • whether a measurement is repeated + same result is obtained
43
Q

reliability
ASSESSING RELIABILITY

A

TEST-RETEST: same test/questionnaire given to the same person on 2 / more different occasions
- result should be similar

INTER-OBSERVER: compare observations from different observers in a pilot study of the same event

measuring reliability: 2 sets of data are correlated
- correlation coefficient should exceed + .80 for reliability

44
Q

reliability
IMPROVING RELIABILITY

A

rewriting questions in questionnaines:

  • replacing some open qs (can be misinterpreted) w closed qs
  • improve training / use same person for interviews
  • standardised procedures in experiments - strict control over instructions + conditions
  • operationalisation of behevioural categories in observation
  • behavioural categories should be measurable + not overlap
45
Q

validity

A

is result legitimate?
- whether

ECOLOGICAL validity: do findings generali re no other rething (eneryday life?
TEMPORAl validity: do findings remain true oner vime ?

46
Q

validity
ASSESSING VALIDITY

A

FACE VALIDITY - achieved by ‘eyeballing’ measuring instrument OR passing it on to an expert to check

CONCURRENT VALIDITY - test is administered to group of ppts + scores are compared w findings of a well-established test
- correlarion should exceed + .80 for validity

47
Q

validity
IMPROVING VALIDITY

A
  • in experiment - [control group, - increases confidence that chayes in DV anedue weffec of IV + srandardisarion.
  • questionnaines - vie scales control Grether of social desirabilin bior + confidenialing is alsoned for all data submitted. pox ambigusol/ofes
  • observarions - behavioural caregories ane operarionalised + mell defined
  • qualitarine nesearch - interpretive validin + tiangularion
48
Q

reporting psychological investigations

A
  • ABSTRACT: short summary of the study including all major elements:
  • aim, hypotheses, method, results + conclusion.
  • INTRODUCTION: literature review - a look at relevant theories, concepts + studies related to study
  • METHOD: should include sufficient detail for replication incl:
  • design, sample, apparatus, procedure, ethics
  • RESULTS: summary of key findings from investigation, including:
  • descriptive stats: eg tables, graphs + charts, measures of central tendency + dispersion
  • inferential stats: reference is choice of stats test, calculate + critical values, significance level + final outcome
  • DISCUSSION:
  • REFERENCING:
49
Q

features of science
PARADIGM

A
  • shared set of assumptions + methods
  • KUHN suggested this was what separated scientific + non-scientific principles
  • argued that psychology lacks a universally accepted paradigm + is best seen as a pre-science, unlike natural sciences eg biology
  • paradigm shifts occur when there is a scientific revolution
  • where a handful of scientists begin to question the accepted paradigm when there is too much contradictory evidence to ignore
50
Q

features of science
THEORY CONSTRUCTION

A
  • theory = set of general laws/principles that have the ability to explain particular events or behaviours
  • testing a theory depends on being able to make clear + precise predictions on the basis of the theory (ie to stae a no of possible hypotheses)
  • a hypothesis can then be tested using scientific methods to determine whether it will be supported or refused
  • the process of deriving a new hypothesis from an existing theory is known as deduction
  • bottom up + top down
51
Q

features of science
falsifiability

A
  • popper argued that the key criterion of a scientific theory is its falsifiability
  • genuine scientific theories could hold themselves up for hypothesis testing + the possibility of being proved false
  • popper distinguished between theories which can be challenged + what he called ‘pseudosciences’ which couldn’t be falsified
  • he believed that even when a scientific principle had been successfully + repeatedly tested, it was not necessarily true
  • instead, it had simply not been proved false (yet)

eg psychodynnamic approach

52
Q

features of science
REPLICABILITY

A
  • testing the validity of research results
  • if a scientific theory is to be trusted, the findings from it must be shown to be repeatable across a no of different contexts
  • by repeating a study, we can see the extent to which the findings can be generalised
53
Q

features of science
OBJECTIVITY

A

to reduce bias in research
* scientific researchers must keep a ‘critical distance’ during research
* musn’t allow personal opinions/biases to ‘discolour’ the data or influence the behaviour of ppts
* methods associated w greatest level of control, eg lab studies, tend to be th most objective

54
Q

features of science
EMPIRICAL METHODS

A
  • emphasise the importance of data collection based on direct, sensory experience
  • experimental + observational method are good examples of empirical method in psychology
  • early empiricists, eg John Locke saw knowledge as determined only by experience + sense perception
  • a theory cannot be claimed to be scientific unless it has been empirically tested + verified
55
Q

the sign test

A
56
Q

levels of measurement

A
57
Q

probability + significance

A
58
Q

statistical tests

A

psych (11 decks)

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