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
2
Q
independent groups
A
where each participants only takes part in one condition of the experiment
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
4
Q
repeated measures
A
where each participant takes part in all conditions of the experiment
5
Q
evaluation of repeated measures
A
+ fewer participants
+ decreased effects of individual differences
- increased chance of demand characteristics
- increased chance of order effects
6
Q
matched pairs
A
where participant are matched based on a relevant characteristic and put in separate conditions
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
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
9
Q
field experiment
A
conducted in a natural environment
+ ecological validity
+ reduced demand characteristics
- less control
- ethics, harder to consent
10
Q
natural experiment
A
IV isn’t manipulated, it’s an event
+ ethical
+ ecological validity
- variables, harder to establish causal relationships
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
12
Q
What is a hypothesis?
A
A precise and testable statement of the relationship between two variables
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
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
15
Q
Null hypothesis
A
Stating that there will not be a difference/correlation between variables
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
17
Q
difference between aim and hypothesis
A
aim is generic, outlines focus
hypothesis is precise, IV and DV operationalised
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
19
Q
Evaluation of random sampling
A
+ unbiased, each person has equal chance
- impractical, may be very large target group
20
Q
Systematic sampling
A
- put sample in a list
- chose every nth person (eg every 4th)
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)
22
Q
Stratified sampling
A
Sample should be representative of target population
Target group info sections based on key characteristics
- eg is 60% males
23
Q
Evaluation of stratified sampling
A
+ representative
- more time and resources
24
Q
Opportunity sampling
A
Uses participants who are both accessible and willing to take part
25
Evaluation of opportunity sampling
+ cheap and easy
- may not be representative and bias
26
Volunteer sampling
Uses people who have volunteered to take part
27
Evaluation of volunteer sampling
+ achieve large sample, reaches wide audience
+ easy
- certain type of people likely to volunteer, unrepresentative
28
What are participant variables?
Changes to or differences in the participants that affect the results
29
what are participant effects?
caused by participant variables
demand characteristics - act unnaturally as being studied
social desirability bias - want to look good in society
30
What are investigator effects?
Ways in which the researcher can affect the performance or behaviour of participants
eg change behaviour or leading questions
results in demand characteristics
31
What is researcher bias?
researchers expectations can influence results
influences design or behaviour towards participants
influence how to analyse the data
32
What is operationalisation?
Making variables measurable and specific
33
Independent variable
Thing you change between conditions
34
Dependant variable
Thing you measure
35
Extraneous variables
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)
36
Confounding variable
3rd variable in a correlation that affects the other variables
37
Ways of controlling variables
- random allocation
- counter balancing
- standardisation
- randomisation
38
What is random allocation?
Assigning participants to conditions randomly
Reduces extraneous variables
- ensures no bias
39
What is standardisation?
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
What is counterbalancing?
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
what is randomisation?
deliberate avoidance of bias
participants given materials in random order
- avoids order affects
42
What is a pilot study?
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
What is reliability? + types
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
Ways to assess reliability
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
Improving reliability
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
What is validity?
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
Types of validity
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
Ways of assessing validity (internal)
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
what affects validity?
demand characteristics
- when participants act in unnatural ways as they are in an experiment
investigator effects
- when research impacts of behaviour of participants
50
Ways in improving validity
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
observations
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
non-participant observations
researcher observes, without getting involved
+ researcher can remain objective
+ less risk of investigator effects
- doesn't form a relationship, less understanding of behaviour
53
participant observations
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
overt observations
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
covert observations
researcher isn't known to participants - don't know they are being studied
+ demand characteristics less likely
- less ethical, can't consent
56
controlled observations
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
naturalistic observations
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
what is observational design?
choice of behaviour to record and how its measured
59
behavioural categories
operationalised behaviours the researchers look for
- specific and clearly defined so can't be confused
60
sampling methods in an observation
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
questionnaires
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
interviews
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
what is content analysis?
- 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
evaluation of a content analysis
+ 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
what is a meta-analysis?
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
Case studies
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
primary data
information collected by the researcher themselves in a study
68
secondary data
information collected from other studies
can be used for evidence or check validity
69
measures of central tendency
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
measures of dispersion
range - highest minus lowest
+ easy to calculate
- skewed
standard deviation - measures spread of data around the mean
+ not skewed
- harder to calculate
71
what is a correlation?
measure of the relationship between two variables
72
what is the correlation coefficient?
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
advantages of correlational research
+ 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
disadvantages of correlational research
- cant establish cause and effect
correlation doesn't mean causation
- difficult to interpret, correlation may be due to chance
75
what is distribution?
graph plotted to show average spread of data
can be normal or skewed
Mode is the hump
76
normal distribution
symmetrical around the mean
- shown as bell curve
- width of curve depends on SD
mean = median = mode
77
positively skewed distribution
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
negatively skewed distribution
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
when would you use a table?
quantitative data
- show patterns
80
when would you use a line graph?
continuous data
shows change over time
IV on X and DV on Y
81
when would you use a bar chart?
non- continuous data (data in categories)
shows difference between distinct conditions
82
when would you use a scattergram?
to tell if two variables are related
- showing correlations
83
when would you use a histogram?
difference between conditions
IV is continuous data
84
difference between continuous and non-continuous data
continuous - data that falls of a scale
eg height
non-continuous - data that falls into distinct categories
eg ice cream flavours
85
structure of a psychological report
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
peer review process
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
purposes of peer review
- 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
what are the implications of research on the economy?
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
What must be included for a study to be ethical?
- 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
dealing with ethical issues
- 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
what is a thematic analysis?
method used to analyse qualitative data
identify, analyse and report common themes from the data set
92
how is a thematic analysis done?
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
evaluation of a thematic analysis
+ 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
evaluation of quantifying data
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
