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AQA Psych for advanced info only > Research Methods P2 > Flashcards

Research Methods P2 Flashcards

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1
Q

Hypothesis

A

-Clear, Precise and testable statement
Should be operationalised - how you will measure …
-states what variables to be investigated
-stated at start of the study

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2
Q

Directional Hypothesis

A

-One tailed
States direction of the difference
ex. More than
Done when there is previous similar research
There is a a positive difference between IV and the DV…

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3
Q

Non-Directional Hypothesis

A

-Two tailed
States a difference between two variables
The is a difference between IV & DV

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4
Q

Aim

A

A general expression of what the researcher tends to investigate
-The PURPOSE

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5
Q

Independant Variable

A

-Manipulated by researcher to investigate the effect on The DV

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6
Q

Dependant Variables

A
  • What the researcher is measuring

- Effected by change in IV

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7
Q

Extraneous Variables

A
  • nuisance variables -> harder to find result/ detect the effect
  • Must attempt to control EV’s
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8
Q

Participant Variables

A
  • Type of Extraneous Variable

- Features of the participant, individual differences -> e.g. a persons mood

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9
Q

Situational Variables

A
  • type of EV

- Features of the situation, e.g. are the instructions standardised?

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10
Q

Confounding Variables

A

When SV and PV occur at the same time as IV, they become Confounding Variables

  • Change systematically with the IV
  • Must be controlled
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11
Q

Operationalisation

A
  • what the variables are defined by

- How they will be measured

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12
Q

Demand Characteristics

A

refer to any cue given by the researcher or situation, that may reveal the aim of the study & change participant’s behaviour

  • > ‘SCREW -U’ effect - underperform
  • > ‘PLEASE-U’ effect - overperform
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13
Q

Investigator effects

A

Any effect of the investigators behaviour on the outcome of the research, the DV, or design decisions

->’Expectancy effects’ is where the investigator provides unconscious clues

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14
Q

Randomisation

A

the use of chance when designing investigations to control for the effects of bias

e.g. random allocation of participants to conditions

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15
Q

Standardisation

A
  • using the exact same formalised procedures for all participants in a research study
  • if not differences can become EV’S
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16
Q

Hypothesis writing tips

A
  • is the IV and DV clear & measurable
  • are the differences in direction between IV & DV mentioned
  • Is it two tailed or one tailed
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17
Q

Experimental Design

A

different ways of organisation for testing participants (RIM’ed)

  • Independant groups
  • Repeated Measures
  • Matched Pair Design
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18
Q

Independant groups

A

-One group does Condition A the other does condition B
-PPTS are randomly allocated to experimental groups
+ no order effects -> tested 1, can’t practise/get tired, will not guess the aim ->behaviour more ‘natural’ -higher realism

  • participant variables, ppts in 2 groups are different -> acting as EV/CV -> reduce validity
  • Less economical -> more expensive than if done once as more ppts needed and more time used recuiting -expensive
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19
Q

Repeated Measures

A
  • All ppts take part in all conditions of an experiment
  • Order of conditions should be counterbalanced -> avoid order effects

+ participant variables, the people in both conditions have the same charachteristics
+ Fewer participants -> more economical as saves time recruiting and money spent

  • order effects, may do worse/better when doing similar task twice ->practise/fatigue effects
  • Ppts guess aims -> reduce validity of the results as a change in behaviour
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20
Q

Matched Pair design

A

-2 groups of participants - related as paired on participant variables
+matched on variables relevant -> control ppt variables & enhances the validity
+no order effects -> only doing condition once -> no fatigue/practice effects
- matching isn’t perfect as time consuming
-need twice as many ppts than RM for same data -> time spent recruiting

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21
Q

Laboratory experiment

A
  • controlled environment, EV & CV regulated
  • ppts go to researcher
  • IV is manipulated -> effect on EV is recorded

+EVS & CVs can be controlled -> effects are minimised -> cause & effect between IV and DV can be demonstrated -> high internal validity
-lacks generalisability -> artificial tasks & ppts may be aware that they are changing the study -> low external validity

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22
Q

Field Experiment

A

a natural setting, researcher goes to participants
-IV is manipulated & effect on DV is recorded

+more natural -> produce more authentic behaviour -> more generalisable
+ppt’s are unaware they are being studied -> no change in behaviour due to demand characteristics ->greater external validity
- more difficult to control CV/EVs -> changes in DV = CV/evs -> hard to establish cause & effect

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23
Q

Natural experiment

A

-IV is not manipulated, changes naturally -> it will change without an experimenter.
-IV varies
-DV is naturally occurring or may be devised by experimenter & measured in a field/lab
+only practical/ethical option, greater external validity ->involves real-world issues like stress & exams ->more relevant & valid
-natural event may be rare, ppt’s aren’t randomly allocated

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24
Q

Quasi experiment

A

IV based on pre-existing difference between ppl e.g. gender -> just exists

DV can be naturally occurring or devised by the experimenter and measured in field/lab
+high control, comparisons can be made between people
-ppt’s not randomly allocated, casual relationships not demonstrated

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25
Q

Population

A

the large group of people that a researcher is interested in studying

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26
Q

Sample

A

smaller group of larger population selected to take part in the study

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27
Q

Generalisation

A

sample should be representative of population so generalisations can be made

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28
Q

Bias

A

Most samples are biased in that certain groups may be under or over represented

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29
Q

Random sample

A

every person in target population has an equal chance of being selected
- by lottery method, all members of TP are given a number and placed in a hat/computer randomiser used

+potentially unbiased -> EVs/CVs are controlled -> enhances internal validity
-time consuming, lists are hard to get, ppt’s may refuse to take part

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30
Q

Systematic Sample

A

ppt’s are selected by using a ‘set’ pattern.
-every Nth person is selected from a list of the target population
+unbiased -> selected at random as it is an objective method
-time and effort -> could just use random

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31
Q

Stratified sample

A

-The sample represents proportions of people in certain subgroups within population
-subgroups are identified -> percentages of subgroups are reflected in the sample
+ representative method,
- stratification is not perfect

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32
Q

Opportunity sample

A

people who are most available -> easier to obtain
-ask ppl nearby to participate
+quick method -> cheaper
- invetiably biased -> unrepresentative of TP as it’s from one area e.g. street

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33
Q

Volunteer sampling

A

-uses participants which select themselves
-by advertising in media e.g. newspapers
+ppt’s are willing -> engage more
- volunteer bias -> share certain traits -> respond to cues & generalisation is limited

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34
Q

Ethical issues

A
  • when a conflict exists between the rights of a participants and the aims of the research
  • BPS code of conduct is a quasi-legal document to protect ppts
  • Respect, Competence, Responsibility and Integrity
  • Committees weigh up costs & benefits of the study to decide whether it proceeds
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35
Q

Informed consent

A
  • ppt’s make a informed judgement about whether to take part
  • may reveal the aims
  • seek consent forms, appropriate seek parental consent
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36
Q

Types of consent

A
  • Presumptive: ask a similar group and assume the ppt’s agree
  • Prior general: agree to be deceived
  • Retrospective: Get consent after the study
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37
Q

Deception

A
  • issue is deliberately misleading or withholding information so consent is not informed, mild deception is okay
  • should be debriefed & told the real aims, details that weren’t given during study, what their data will be used for and the right to withhold data
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38
Q

Protection from Harm

A
  • issue is that participants should be at no more risk than they would be in everyday life
  • given right to withdraw at any stage
  • should be reassured of their behaviour & that it was normal during debriefing
  • Researcher should provide counselling if distress in ppt’s
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39
Q

Privacy & confidentiality

A
  • the issue is that we have the right to control information about ourselves -> invaded = confidentiality should be respected
  • held personal details must be protected, researchers refer to ppt’s using numbers, initials or false names
  • personal data can’t be shared with other researchers
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40
Q

Correlation

A

illustrates the strength & direction of an association between two co-variables

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41
Q

Scattergram

A

one co-variable is on x-axis

other on y-axis

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42
Q

Types of correlation

A

-Positive = co-variables increase together
-Negative = one co-variable increases as one decreases
-0 correlation = no relationship between variables
on scale from -1 to +1 if close to one the correlation is stronger -> more significant

if further away from one the correlation is weaker -> less significant

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43
Q

Experiment vs Correlation

A

experiment - Researcher manipulates IV and records effect on DV
correlation - no manipulation of variables, cause & effect no demonstrated

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44
Q

Correlation evalution bp

A

+Useful starting point for research -> provides a measure of how two variables are related -> suggest hypotheses
+ relatively economical ->no need to control variables & use secondary data -> less time consuming than experiements
-no cause & effect -> presented as casual as only show how 2 variables are related -> false conclusions
-intervening variables, have untested variables which are involved -> false conclusions

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45
Q

Observational techniques

A
  • way of seeing or listening to what people do without having to task them
  • Often used as a way of assesing the DV

+capture what people do -> ppl act differently from self-reports -> provide insight into behaviour
-risk of observer bias -> may interpret situations differently due to expectations -> bias can reduce by using 2 observers

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46
Q

Naturalistic -OT

A

Takes place where target behaviour will usually occur
+High external validity -> more generalisable
- Low control -> can be uncontrolled CVs/EVs -> more difficult to detect patterns

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47
Q

controlled -OT

A

-some control/manipulation of variables including control of CVs/EVs
+can be replicated -> easily repeated due to standardised procedures -> check findings
-low external validity -> can’t be applied

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48
Q

Covert -OT

A

-participants are unaware they are being studied
+ demand characteristics reduced -> behaviour is natural -> increases internal validity
-ethically questionable -> ppl may not want to be recorded -> participants right to privacy

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49
Q

Overt -OT

A

-participants are aware they are being studied
+ethically acceptable -> informed consent -> right to withdraw
-demand characteristics -> knowledge of being studied influences behaviour -> reduces internal validity

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50
Q

Participant observation

A

-researcher becomes part of group they are studying
+ greater insight -> R experiences situation as participants do -> enhances external validity
-loss of objectivity -> R may identify too strongly with group -> threatens objectivity & internal validity

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51
Q

Non-Participant observation

A

-researcher remains separate from the group they are studying
+ more objective -> researcher maintains objective distance, less chance of bias -> increase internal validity
-loss of insight -> reduce external validity

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52
Q

Behavioural categories - observational design

A
  • the target behaviour to be observed should be broken up into a set of observational categories
  • difficult to make clear & unambiguous -> categories must not overlap
  • dustbin categories -> all forms of behaviour should be in the list
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53
Q

Event sampling -OD

A

-a target behaviour/event is recorded everytime it occurs
+ useful for infrequent behaviour that could be easily missed in time sampling
- complex behaviour oversimplified -> important details go unrecorded -> affect validity of findings

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54
Q

Time sampling -OD

A

-observations are made at regular intervals e.g. once every 15 seconds
+reduces number of observations -> data recorded at certain intervals -> observation is structured
-unrepresentative - not reflect whole behaviour

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55
Q

Questionnaires - self report techniques

A

a pre-set list of written questions to which a participant responds
+can be distributed to lots of people, straightforward to analyse
-responses may not the truthful -> social desirability bias, response bias -> may favour a kind of response

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56
Q

Interviews - self report techniques

A

face to face/online interaction between an interviewer and interviewee
types: Structured, Unstructured, semi-structured

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57
Q

Structured Interview

A

a list of predetermined questions asked in a fixed order
+easy to replicate -> reduces differences between interviewers
-interviewers can’t elaborate -> limit the richness of data collected

58
Q

Unstructured interview

A

no set questions, general topics discussed
Interaction is free-flowing
Interviewee encourages to elaborate
+greater flexibility -> gains more insight into interviewee’s worldview -> can collect unexpected information.
-Increased risk of interviewer bias

59
Q

Semi-structured interviews

A

A List of questions that have been worked out in advance

but interviewers ask further questions based on given answers

60
Q

Designing questionnaires

A

-avoid jargon
-avoid double barrelled questions
-avoid leading questions
whether you will use closed or open questions?

61
Q

Closed questions

A

-limited choice of responses
-produces quantitive data (numbers, scales) & qualitative data -> convert it
+Easier to analyse ->easier to draw conclusions
-responses are restricted, forces an unrepresentative answer -> reduces the validity of the findings.

62
Q

Open questions

A

-respondent provides own answers expressed in words
-produces qualitative data (opinions)
+responses not
restricted -> have more external validity
-difficult to analyse -> forced to reduce data to statistics

63
Q

Designing interviews

A

A standardised list of questions that needs to be covered -> reduce interviewer bias

  • a quiet room will encourage the interviewee will open
  • Begin with neutral questions -> ppt’s relaxed
  • Remind interviewees that answers will be treated in confidence
64
Q

Pilot studies

A

A small scale trial run of a research design using a small number of participants
-used to find out if certain things don’t work so you can correct them before spending time & money

65
Q

Qualitative data

A

non-numerical data expressed in words
+richness of detail ->more meaningful leading to greater external validity
-Difficult to analyse -> leads to subjective interpretation & researcher bias.

66
Q

Quantitative data

A

numerical data
+easier to analyse
-Narrower in meaning -> lower external validity

67
Q

Primary data

A

-first hand data collected for the purpose of the investigation
+fits the job -> info is directly relevant to research aims
-requires time & effort -> secondary data can be accessed within minutes

68
Q

Secondary data

A

-collected by someone other than the person who is conducting the research
+inexpensive -> requires minimal effort
-Quality may be poor ->information may be outdated -> challenges the validity

69
Q

Meta-analysis

A

a type of secondary data, involves combining data from a large number of studies.
+increases the validity of conclusions -> increases the extent to which generalisations can be made
-publication bias ->therefore conclusions may lack validity

70
Q

Measures of central tendency

A

mean
median
mode

71
Q

Mean

A

an average
-add up all scores & divide by the number of scores
+sensitive measure -> includes all scores in data -> representative
-can be unrepresentative ->one extreme result can distort the mean

72
Q

Median

A

the middle value
places scores in ascending order & select middle value
if two median values use the mean of both
+Less affected by extreme scores
-less sensitive than the mean

73
Q

Mode

A

most common value, used in nominal data
+relevant to categorical data
-overly simple measure -> not useful when many modes

74
Q

Measures of dispersion

A

range

standard deviation

75
Q

Range

A

difference between highest and lowest score
+easy to calculate
-doesn’t account for the distribution of the scores

76
Q

Standard deviation

A

Measure of the average speed around the mean
larger the standard deviation, the bigger the spread of data
+more precise than the range
-it may be misleading

77
Q

tables

A

raw scores displayed in columns & rows

a summary paragraph beneath explains the findings & draws conclusions

78
Q

Bar charts

A

categories are placed along the x-axis and frequency on the y-axis

the height of each column represents the frequency of that item

79
Q

Histograms

A

bars touch each other
data is continuous
a true zero

80
Q

Scatter grams

A

used for correlational analysis
each dot represents one pair of related data

illustrates strength & direction of correlation

81
Q

Normal distributions

A

symmetrical, bell-shaped curve
most items are in the middle area of the curve
mean,median,mode occupy the same mid-point of the curve

82
Q

Skewed distributions

A

distributions that lean to one side because most items are either at the lower or upper end of the distribution

83
Q

Negative skew

A

-distribution is towards the right of the graph, resulting in a long tail on left
mode is highest peak, median in middle and mean is dragged left

84
Q

Positive skew

A
  • most of distribution is towards the left of the graph, resulting in a long tail on the right
  • mode is highest point, median is middle, the mean is dragged to right
85
Q

significance

A

-Significance, the difference between two sets of data is greater than what would occur by chanc

86
Q

Probability

A
  • about how likely it is that a certain event will happen if the null hypothesis were true
  • accepted at 0.05
87
Q

sign test

A

-analyse related designs with nominal data
-tests a difference
Subtract B from A -> produce the sign of difference
Add up - &+
Omit those who stay the same -> deduct from N
S value is total of the less frequent sign
if S is equal or less than critical value, S is significant

88
Q

Peer review

A
  • before publication, all aspects of the investigation are scrutinised by experts in the field
  • objective
  • peer should be unknown to researcher
89
Q

Peer review aims

A

funding: allocate research funding
validation of the quality & relevance of the study
Improvements & amendments are suggested

90
Q

peer review eval

A

+protects quality of published research -> minimises possibility of fraudulent research -> preserves reputation of psychology as a science

  • anonymity can be used criticise rival research
  • Publication bias
  • Ground breaking research may be buried
91
Q

the economy

A
  • findings of psychological research can benefit our financial prosperity
    e. g. Attachment research into the role of father, stressed role of father, promotes flexible working arrangements -> contribute to economy
    e. g. The development of treatment for mental disorders, a 3rd of all days off work are caused by mental disorders, better access to therapy or psychotherapeutic drugs ->ppl can manage their mental health ->contribute to economy
92
Q

correlation

A 
an association between two co-variable
use scatter gram to plot
coefficient = strength
positive if number =+X
Negative if number = -X
strength depends on closeness to 1 - if further = weak
93
Q

Case studies

A
  • idiographic
  • detailed, in depth & longitudinal
  • analysis of individual, group or institution.
  • unusual events within a person
  • qualitative data through case history collecting data from questionnaires, interviews etc..
94
Q

case studies eval

A

+provides rich, detailed insight ->as more detail it can increase validity of data
+enables study of unusual behaviour -> some conditions are rare and this will help understanding of an individuals typical functioning
-prone to researcher bias ->uses subjective interpretation ->reduce the validity
-small samples -> studies only a small group/ individuals with unique charachteristics -> low external validity as we can’t generalise to whole populations

95
Q

content analysis

A

ppl studied indirectly through communications

  • type of observational research
  • e.g. Spoken interaction.
96
Q

content analysis -coding

A

coding - information is categorised into meaningful units

can involve counting up the number of times a particular word

97
Q

thematic analysis

A

more qualitative
produce themes - more descriptive
can be categorised into broader categories

98
Q

content analysis eval

A

+many ethical issues don’t apply -> material studied may already be in public domain ->no issues with obtaining consent.
+ flexible method ->produce both Quantitative & qualitative data -> can be adapted to suit the aims
-communication is studied out of context -> may attribute motivations to speaker that aren’t intended ->reduce the validity of conclusions drawn
-may lack objectivity -> threatens the validity of the findings

99
Q

reliability

A

the measure of consistency, if a measurement is repeated and the sane result is obtained, then it is reliable

100
Q

assesing reliability

A
  • test then retest -> test same person twice -> results should be similar each time
  • inter-observer, compare observations between two or more observers -> conduct a pilot study to test that observers are applying the same behavioural categories
  • use a correlation -> should be +0.80 or more for reliability
101
Q

improving reliability

A
  • questionnaires -> rewrite open questions to closed, fixed choices -> less ambiguous.
  • interviews -> improve training and try use same interviewer each time
  • observations -> operationalise the behavioural categories =measurable, no overlapping - may be inconsistent judging.
  • experiments -> use standardised procedures
102
Q

validity

A

is the result legitimate?

whether an observed effect is genuine & represents what is seen in the real world.

103
Q

internal validity

A

control within a study e.g. demand characteristics

104
Q

external validity

A

generalising to other settings, populations or eras

105
Q

ecological validity

A

whether findings can be generalised from one setting to another
-relates to the realism of the ppt’s task

106
Q

temporal validity

A

findings should be consistent over time

e.g. Asch’s study lacks temporal validity because it was conducted during a conformist era in US history

107
Q

face validity

A
  • way to asses validity
  • a test looks like it measures what it claims to do
  • done by measuring the instrument or getting an expert to check
108
Q

concurrent validity

A

whether findings are similar to those on a well-established test

109
Q

improving validity

A
  • experiements -> control group (the researcher is sure that changes in dv were due to effect of the IV) & standardised procedures
  • Questionnaires -> use a lie scale to control for effects of social desirability bias -> use confidentiality to assure respondents of their privacy
  • observations -> use good categories = well defined, operationalised
  • qualitative research -> triangulation (multiple sources of evidence)
110
Q

statistical tests

A

determine whether a difference/ or association found in an investigation is significant

111
Q

Chi squared

A
  1. Test of difference, unrelated design and nominal data

2. Test of correlation, nominal data

112
Q

Sign Test

A
  • Test of difference
  • related design
  • nominal data
113
Q

Mann-whitney test

A
  • test of difference
  • ordinal data
  • unrelated design
114
Q

Wilcoxon test

A
  • test of difference
  • ordinal data
  • related design
115
Q

Spearmans Rho test

A
  • test of correlation

- ordinal data

116
Q

Unrelated t test

A
  • test of difference
  • unrelated design
  • interval data
117
Q

Related t test

A
  • test of difference
  • related design
  • interval
118
Q

Pearsons R

A

Test of correlation

Interval data

119
Q

Nominal data - level of measurement

A

each item can appear once in one category
no order
categories

120
Q

ordinal data - lom

A
  • numerical data, in ordered scale but intervals vary

- based on opinion, emotion and is abstract -> subjective

121
Q

Interval data -lom

A
  • numerical scales with equal units

- better than ordinal as more detail is preserved

122
Q

Probability

A

the null hypothesis is accepted or rejected at a level of 0.05 or 5% probability of the event occuring

123
Q

Significance

A

if not significant, the null hypothesis is accepted - ‘no difference/ correlation’

124
Q

Type 1 error

A

null hypothesis is accepted & alternative hypothesis is rejected but null hypothesis is ‘true’
a false positive - optimistic as significant d/c is found when it =0

125
Q

Type 2 Error

A
  • null hypthesis is accepted, but the alternative hypothesis is true
  • pessimistic error
  • false negative
126
Q

Errors & likilihood

A
  • type 1 = if significance level is too lenient like 0.1

- type 2 = if significance is too strict like 0.01, potential values can be missed

127
Q

sign test method

A
  1. enter pairs of related data into a table
  2. for each pair, score plus or minus
    - = if item 2 is larger than item 1, + = if item 1 is larger than item 2
  3. S= the number of less frequent sign
  4. use critical value to calculate significance
128
Q

scientific report sections

A
  • abstract
  • introduction
  • method
  • results
  • discussion
  • referencing
129
Q

Abstract - sr

A

a short summary that includes aims, hypotheses, method, results and conclusions

130
Q

Introduction-sr

A
  • looks at relevant theories, concepts and studies

- follow logical progression, start broad then specific

131
Q

Method -sr

A
  • other researchers should be able to replicate study
  • include the design +justifications, sample, sampling method, target population, apparatus and materials, procedure, ethics
132
Q

Results - sr

A

-summary of key findings
-include descriptive statistics, inferential statistics
with the final outcome& any raw data.

133
Q

Discussion - SR

A
  • summary of findings in writing
  • relationship of the results to previous research
  • Limitations, suggestions to change
  • wider real-world implications of the research
134
Q

Referencing

A
  • reference journal articles including author, date etc..
  • reference books, authors, dates, publisher etc..
  • reference web sources
135
Q

features of a science

A
  • paradigm & paradigm shifts
  • theory construction
  • falsifiability
  • Replicability
  • Objectivity
  • Empirical method
136
Q

Paradigms

A

Kuhn 1962 - a paradigm is a shared set of assumptions and methods, psych = pre-science -> lack of universally accepted paradigms

137
Q

Paradigm shifts

A
  • occur when there is scientific revolution

- researchers questions the accepted paradigm when there is too much contradictory evidence to ignore.

138
Q

Theory construction

A
  • a set of general laws/ principles that have the ability to explain particular events/behaviours
  • need clear & precise statements to test
  • deduction = deriving a new hypothesis from an existing theory
139
Q

Falsifiability

A
  • popper 1934, the key criteria of a scientific theory is its falsifiability
  • should be used to test hypothesis and have the possibility of being proved false
  • If cant be falsified & tested -> Pseudoscience
140
Q

Replicability

A
  • the findings of a theory must be shown to be repeatable across a number of different contexts
  • replicability allows us to see the extent of which the findings can be generalised
141
Q

Objectivity

A
  • researchers keep a distance during research -> not allow personal opinions/biases to change the data
  • methods with high control are the most objective
142
Q

Empirical method

A

-data collection based on direct, sensory experience
-experimental & observational method = good examples
a theory can’t claim scientific unless it has been empirically tested

AQA Psych for advanced info only (11 decks)

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