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Psychology P2 > Research Methods - Y12 > Flashcards

Research Methods - Y12 Flashcards

1
Q

features of science

A

empirisism - belief theories should be supported by observable evidence

falsifiability - theory should state how and be able to be proven wrong

replicability - research should be repeated in same way with same results

objectivity - research remain impartial, avoid subjective interpretation, facts not opinions

hypothesis testing - create explanations and predictions for findings and test them scientifically

paradigms and shifts - widely held beings about how things work, shifts are when discoveries change these

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2
Q

independent groups

A

where each participants only takes part in one condition of the experiment

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3
Q

evaluation of independant groups

A

+ less chance of demand characteristics
+ decreased chance of order effects

  • needs more participants
  • increases effects of individual difference
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4
Q

repeated measures

A

where each participant takes part in all conditions of the experiment

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5
Q

evaluation of repeated measures

A

+ fewer participants
+ decreased effects of individual differences

  • increased chance of demand characteristics
  • increased chance of order effects
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6
Q

matched pairs

A

where participant are matched based on a relevant characteristic and put in separate conditions

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7
Q

evaluation of matched pairs

A

+ less chance of demand characteristics
+ decreases effects of individual differences
+ decreases chance of order effects

  • more participants needed
  • hard to match on certain criteria
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8
Q

lab experiments

A

conducted in an artificial setting
control all variables accept the IV

+ control
+ replication
+ establish causal relatioships

  • lack ecological validity, artificial
  • demand characteristics
  • ethics, deception
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9
Q

field experiment

A

conducted in a natural environment

+ ecological validity
+ reduced demand characteristics

  • less control
  • ethics, harder to consent
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10
Q

natural experiment

A

IV isn’t manipulated, it’s an event

+ ethical
+ ecological validity

  • variables, harder to establish causal relationships
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11
Q

quasi experiment

A

IV is a characteristic of the participant

+ control
+ ecological validity, less artificial

  • can’t randomly allocate participants, confounding variables may impact it
  • harder to establish causal relationships
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12
Q

What is a hypothesis?

A

A precise and testable statement of the relationship between two variables

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13
Q

Directional hypothesis

A

Stating that there will be a difference/correlation between condition
Stating which group will perform better - direction
(or what the correlation is)

Use if previous research

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14
Q

Non-directional hypothesis

A

Stating that there will be a difference/correlation between conditions
Not saying which group will perform better (or what the correlation is) - no direction

Use when there is NO previous research

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15
Q

Null hypothesis

A

Stating that there will not be a difference/correlation between variables

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16
Q

what is the aim of an experiment?

A

generic statement about what the researcher intends to study, generated from a theory

what is being studied and what it is tying to achieve

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17
Q

difference between aim and hypothesis

A

aim is generic, outlines focus

hypothesis is precise, IV and DV operationalised

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18
Q

Random sampling

A

Gives every member of a target population equal chance in being selected

  • assign each member a number
  • use random generator to chose
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19
Q

Evaluation of random sampling

A

+ unbiased, each person has equal chance

  • impractical, may be very large target group
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20
Q

Systematic sampling

A
  • put sample in a list
  • chose every nth person (eg every 4th)
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21
Q

Evaluation of systematic sampling

A

+ unbiased, as long as list is in random order

  • may be bias if list has an order (or list is only male)
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22
Q

Stratified sampling

A

Sample should be representative of target population
Target group info sections based on key characteristics
- eg is 60% males

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23
Q

Evaluation of stratified sampling

A

+ representative

  • more time and resources
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24
Q

Opportunity sampling

A

Uses participants who are both accessible and willing to take part

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25
Q

Evaluation of opportunity sampling

A

+ cheap and easy

  • may not be representative and bias
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26
Q

Volunteer sampling

A

Uses people who have volunteered to take part

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27
Q

Evaluation of volunteer sampling

A

+ achieve large sample, reaches wide audience
+ easy

  • certain type of people likely to volunteer, unrepresentative
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28
Q

What are participant variables?

A

Changes to or differences in the participants that affect the results

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29
Q

what are participant effects?

A

caused by participant variables

demand characteristics - act unnaturally as being studied

social desirability bias - want to look good in society

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30
Q

What are investigator effects?

A

Ways in which the researcher can affect the performance or behaviour of participants

eg change behaviour or leading questions

results in demand characteristics

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31
Q

What is researcher bias?

A

researchers expectations can influence results

influences design or behaviour towards participants

influence how to analyse the data

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32
Q

What is operationalisation?

A

Making variables measurable and specific

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33
Q

Independent variable

A

Thing you change between conditions

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34
Q

Dependant variable

A

Thing you measure

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35
Q

Extraneous variables

A

Other factors that affect the DV (not the IV)

Participant variables - changes to or differences between participants

Situational variables - changes to environment (common in less controlled methods)

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36
Q

Confounding variable

A

3rd variable in a correlation that affects the other variables

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37
Q

Ways of controlling variables

A
  • random allocation
  • counter balancing
  • standardisation
  • randomisation
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38
Q

What is random allocation?

A

Assigning participants to conditions randomly
Reduces extraneous variables
- ensures no bias

39
Q

What is standardisation?

A

Ensuring experience of participants is exactly the same (except IV)
identical procedure used

Eg standardised instructions, ensure instructions are the same (written not spoken)
timings, materials, sample size etc

reduces variable = more replicable and reliable

40
Q

What is counterbalancing?

A

applies to repeated measures
Get participants to complete conditions in different orders
Eg A - B then B - A

Reduces order effects
eg fatigue, practise

41
Q

what is randomisation?

A

deliberate avoidance of bias

participants given materials in random order
- avoids order affects

42
Q

What is a pilot study?

A

Small scale test prior to main study

Researcher can identify issues and change them - saves time and money in main study

allow validity and reliability to be assessed and improved

43
Q

What is reliability? + types

A

Measure of consistency

When repeated, should get same results

inter-rater
the extent to which 2 DIFFERENT researchers would give the same participant the same score

test-retest
the extent to which the SAME researcher would give the same participant the same score on DIFFERENT occasions

44
Q

Ways to assess reliability

A

Test-retest
- Same participants and researcher repeat more than once
- Shown on scatter graph = correlation
- correlate scores
= strong positive correlation of +0.8 = reliable

Inter-rater
- several researchers agree on behavioual catagories
- they independently assess the same participant
- correlate scores
- coefficient greater than +0.8 = reliable

45
Q

Improving reliability

A

Standardised procedures - experience identical each time
reduces chance of extraneous variables
improve inter-rater

Operationalisation - clearly defining all variables, categories clear and measurable

lab experiment - controlled conditions
reduces extraneous variables

46
Q

What is validity?

A

Results are accurate, measures what it intends to

Internal - extent to which it measures what it intends to
External - extent to which findings can be generalised beyond the study

47
Q

Types of validity

A

internal
face - the extent to which the test measures what it intends to

concurrent - the extent to which there is close agreement between data from new test and data from an established test

external
Population- extent to which findings can be generalised to the targ population

Ecological- extent to which findings can be generalised to a real life setting

Temporal - extent to which findings can to generalised to modern times

48
Q

Ways of assessing validity (internal)

A

Face validity
- look at it and see if it appears to measure what it intends to

Concurrent validity
- correlate results, test consistency, needed for validity
- must be above +0.8 = valid

49
Q

what affects validity?

A

demand characteristics
- when participants act in unnatural ways as they are in an experiment

investigator effects
- when research impacts of behaviour of participants

50
Q

Ways in improving validity

A

Confidentiality- reduce lying and social desirability bias

Standardisation - reduce variables

double blind - partipants and researcher doesn’t know who in each condition
reduces demand characterisitcs and investigator effects

independent groups reduces demand characteristics

51
Q

observations

A

watching the behaviour of the participants
controlled vs naturalistic
overt vs covert
participant vs non participant

+ observe actual behaviour, less chance of demand characteristics (especially if covert)

  • cant observe peoples thoughts
  • could be effected by researcher bias
52
Q

non-participant observations

A

researcher observes, without getting involved

+ researcher can remain objective
+ less risk of investigator effects

  • doesn’t form a relationship, less understanding of behaviour
53
Q

participant observations

A

when the researcher participates in the activity being studied

+ develops relationship with group being studied, greater understanding of behaviour

  • less objective, may lead to demand characteristics if they know there’s a researcher with them
54
Q

overt observations

A

where the researcher is known to participants - aware they are being studied

+ more ethical, can consent

  • demand characteristics if they know they’re being studied
55
Q

covert observations

A

researcher isn’t known to participants - don’t know they are being studied

+ demand characteristics less likely

  • less ethical, can’t consent
56
Q

controlled observations

A

observations where the researcher can control the conditions
often in a lab setting

+ highly controlled, replicable and more reliable
+ less extraneous variables, can establish cause and effect

  • lower ecological validity
  • demand characteristics
57
Q

naturalistic observations

A

take place in a natural environment, structured so nothing is missed

  • often recorded
  • behaviour categorised - operationalised definition of behaviour
  • may need to rate behaviour
  • decide how often and how long to sample behaviour
  • inter rater reliability
58
Q

what is observational design?

A

choice of behaviour to record and how its measured

59
Q

behavioural categories

A

operationalised behaviours the researchers look for
- specific and clearly defined so can’t be confused

60
Q

sampling methods in an observation

A

time sampling
- records ALL behaviours for a set time, at set intervals

+ easy and convenient
- behaviour outside of time frame missed

event sampling
- only record behaviours they are interested in
- tallies every time that behaviour

+ know what behaviours to look for
- useful behaviours could be ignored

61
Q

questionnaires

A

open questions - can reply in any way
+ detailed information
- hard to analyse

closed questions - quantitative data, yes or no answers
+ easy to analyse
- less detail, eg no reason

don’t use leading questions
avoid ambiguity - be clear

+ quick, can be sent to many people
- easy to lie

62
Q

interviews

A

structured - set questions with closed answers
+ easier to analyse
- less detail

not strctured - few set questions, informal
+ more detail
- harder to analyse, may vary between participants

+ can ask follow up questions
+ build rapport
(unlike questionnaires)
- higher risk of social desirability bias
- time consuming

63
Q

what is content analysis?

A
  • turns qualitative to quantitative data
  • categories identified with operationalised definitions (eg an act of violence)
  • qualitative data analysed to see how often each category occurs
  • statistical analysis then done
64
Q

evaluation of a content analysis

A

+ clearly shows patterns in behaviour
+ can be reliable, as long as categories are clear and operationalised

  • subjective, categories not always clear
  • reducing data to categories reduces detail
65
Q

what is a meta-analysis?

A

analyse results from many studies to draw general conclusions
- collect and collate wide range of previously conducted research

+ creates large sample sizes, more representative
+ avoids individual researcher bias
- can be conflicting results

66
Q

Case studies

A

In depth analysis of one person or a small group

+ rich and detailed data
+ avoid ethical issues, already happened to them

  • can’t generalise
  • time consuming
67
Q

primary data

A

information collected by the researcher themselves in a study

68
Q

secondary data

A

information collected from other studies
can be used for evidence or check validity

69
Q

measures of central tendency

A

mean - average, add all and divide
+ easy
+ includes all numbers in data set = most representative
- skewed by anomalies

median - middle score when in order
+ not skewed
- less reliable as doesnt consider all data in the set

mode - most common
+ not skewed
- less representatie, may be bimodel, less meaningfull

70
Q

measures of dispersion

A

range - highest minus lowest
+ easy to calculate
- skewed

standard deviation - measures spread of data around the mean
+ not skewed
- harder to calculate

71
Q

what is a correlation?

A

measure of the relationship between two variables

72
Q

what is the correlation coefficient?

A

a number between -1 and 1
shows how closely related the variables are

1 or -1 = strong relationship
0 = no relationship

-1 - 0 = negative correlation, one variable rises the other falls (and vice versa)

0 - 1 = positive correlation, variables rise and fall together

73
Q

advantages of correlational research

A

+ doesn’t involve controlling any variables, can be done when it would be unethical to control them
eg research into effects of smoking

+ can be used to test reliability
do a correlation with results from a study, reliable results will give a high correlation

74
Q

disadvantages of correlational research

A
  • cant establish cause and effect
    correlation doesn’t mean causation
  • difficult to interpret, correlation may be due to chance
75
Q

what is distribution?

A

graph plotted to show average spread of data

can be normal or skewed

Mode is the hump

76
Q

normal distribution

A

symmetrical around the mean
- shown as bell curve
- width of curve depends on SD

mean = median = mode

77
Q

positively skewed distribution

A

cluster of scores at lower end of mean
skewed right - tail on the right side

mode (less than) < median < mean

mean greater than median and mode

eg number of children had

78
Q

negatively skewed distribution

A

cluster of scores at the higher end of mean
skewed left - tail on the left side

mode (more than) > median > mean

mean less than median and mode

eg retirement age

79
Q

when would you use a table?

A

quantitative data
- show patterns

80
Q

when would you use a line graph?

A

continuous data
shows change over time
IV on X and DV on Y

81
Q

when would you use a bar chart?

A

non- continuous data (data in categories)
shows difference between distinct conditions

82
Q

when would you use a scattergram?

A

to tell if two variables are related
- showing correlations

83
Q

when would you use a histogram?

A

difference between conditions
IV is continuous data

84
Q

difference between continuous and non-continuous data

A

continuous - data that falls of a scale
eg height

non-continuous - data that falls into distinct categories
eg ice cream flavours

85
Q

structure of a psychological report

A
  1. abstract - summary of whole report (all of the parts below)
  2. introduction - overview of area studied, past theories and studies
  3. method - experimental design, procedure, sample and resources used
  4. results - descriptive (table, graphs) or inferential (statistical tests)
  5. discussion - explain findings and link to past research, limitations and implications of study, suggests fir future research
  6. references - list of resources and information used eg studies
  7. appendices - materials used. raw data and calculations
86
Q

peer review process

A
  1. research creates report
  2. send to academic journals in hopes to be published
  3. rejected or sent to several anonymous researchers
  4. peer evaluate study, suggest and make improvements
  5. researcher makes improvement and resubmits
  6. editor happy = published
87
Q

purposes of peer review

A
  • ensure high quality research published
  • ensures reports communicated appropriately
  • ensures correct decisions (eg design)
  • identify ways in which research can be applied to real life
88
Q

what are the implications of research on the economy?

A

the ways in which research can be applied to real life issues to help society, especially financially

  • practical uses
  • how it effect mentality of public
  • how people can be healthier or more productive
89
Q

What must be included for a study to be ethical?

A
  • informed consent - told aim and agree
  • debrief - told aims, results and uses after
  • confidentiality - data anonymous
  • right to withdraw - be able to leave and results destroyed (know about it)
  • no deception - not lied to
  • protection from harm - not caused distress
90
Q

dealing with ethical issues

A
  • limit deception - should know true aims
  • get informed consent
  • animal rights - cant consent and shouldn’t be harmed, but more ethical than using humans

but can change behaviour if participants know true aims and that they’re being studied

91
Q

what is a thematic analysis?

A

method used to analyse qualitative data
identify, analyse and report common themes from the data set

92
Q

how is a thematic analysis done?

A

researcher views data many times
- becomes familiar with it

look for themes in the data
eg patterns or trends

review and name themes

writes up analysis in report

93
Q

evaluation of a thematic analysis

A

+ subjective so researcher can apply it to a range of theories
+ preserves detail in data

  • research bias as subjective
  • lacks validity as not controlled
  • time consuming
94
Q

evaluation of quantifying data

A

content or thematic analysis

+ easier to see patterns
+ statistical analysis can then be done

  • detail of qualitative data lost
  • can be subjective and open to bias

Psychology P2 (4 decks)

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