research methods Flashcards

(95 cards)

1
Q

hypothesis

A

a clear, precise, testable statement - shows relationship between variables- stated at the outset of any study

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

aim

A

a general statement of the research- the purpose of the study

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

directional hypothesis

A

shows the direction of the difference between 2 conditions
based on previous research findings

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

non-directional hypothesis

A

states that there is a difference between 2 conditions, but direction not specified

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

null hypothesis

A

what is assumed is true during the study
data collected either supports or rejects the null hypothesis
it is often a prediction of no correlation between variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

alternative hypothesis

A

used when the null hypothesis is rejected
can be (non) directional

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

levels of the IV

A

control: without IV
experimental: with IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

operationalisation

A

clearly defining variables in terms of how they can be measured
to make the hypothesis clear and testable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

extraneous variable

A

any variable other than the IV that may have an effect on the DV if not controlled
do not vary systematically with IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

confounding variable

A

essentially an uncontrolled EV
any variable other than the IV that may have affected the DV so that we cannot be sure of the true source of change to the DV
vary systematically with the IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

demand characteristics

A

any cue from the research situation that may be interpreted by participants as revealing the purpose of the investigation
this may lead to participants changing behaviour (please/screw-U)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

investigator effects

A

the effect of the investigator’s (un)conscious behaviour on the DV
may include design, selection, interaction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

randomisaiton

A

the use of chance to control for the effect of bias and investigator effects when designing materials and when deciding the order of conditions
also can avoid order effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

standardisation

A

using exactly the same formalised procedures and instructions for all participants in a study, including the environment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

writing a hypothesis

A
  • state whether there will be a significant difference/ correlation
  • include the IV + DV
    + LEVELS
  • operationalise
  • state direction if necessary
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

experimental design

A

the different ways in which the testing of participants can be organised in relation to the experimental conditions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

types of experimental designs + definitions

A

independent measures: participants allocated to different groups where each group represents 1 experimental condition

repeated measures: all participants in all conditions

matched pairs design: pairs of participants are matched on variables that may affect the DV, one of each pair in each condition
- to control for the confounding variable of participant variables
- may necessitate a pre-test

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

independent measures- evaluation

A

strengths
- no order effects (learning/fatigue)
- only aware of 1 condition- less likely demand characteristics

weaknesses
- participant variables- may cause confounding variables
- no. of participants- 2x as many are needed compared to repeated

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

random allocation

A

to control for participant variables in an independent group design- ensures each participant has the same chance of being in 1 condition as another

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

repeated measures- evaluation

A

strengths
- no participant variables- same people in each condition
- no. of participants is fewer for same amount of data

weaknesses
- order effects- repeating tasks may lead to learning/fatigue effects + demand characteristics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

counterbalancing

A

control for the effects of order in repeated measures
- half experience in 1 order, half in the other

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

matched pairs- evaluation

A

strengths
- no order effects
- participant variables- important differences are minimised by matching

weaknesses
- no, participants- 2x as many needed compared to repeated
- practicalities- time consuming, expensive, difficult to pre-test and identify pairs
- participant confounding variables are still likely

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

in experimental design, consider

A

order effects, participant variables, number of participants, demand characteristics. practicalities

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

types of experiment + definitions

A

lab: in a controlled environment, researcher manipulates IV and records effect on DV, whilst maintaining strict control of EV

field: takes place in a natural setting- researcher manipulates IV and records effect on DV

natural: the change in IV is not brought about by the researcher, but would have happened had they not been present
researcher records effect on DV.
IV = natural and not necessarily the setting so participants can be tested in a lab

quasi: IV is based on an existing difference between people- it is naturally occurirng, such as gender

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
lab experiment- evaluation
strengths - high control over EV- can ensure that any effect on DV is a result of manipulating the IV - can therefore establish cause and effect (causal relationships)- high internal validity - replication = possible due to high control ensures new EV are not introduced when repeating an experiment replication = vital to check whether results are valid weaknesses - may lack generalisability- the lab environment is artificial and therefore does not measure real life behaviour - so lacks ecological validity participants may act in unusual ways due to the context, so their behaviour cannot be generalised outside the research setting- low external validity. - demand characteristics may bias the result as participants may respond to what they thing is being investigated - low mundane realism- tasks are not representative of real life - deception = often used, so informed consent is difficult
26
field experiment- evaluation
strengths - higher mundane realism than lab- natural setting increases ecological validity - demand characteristics can be avoided if participants are unaware they are in a study, increases internal validity - can still establish causal relationships by manipulating IV and measuring DV weaknesses - less control over EV- confounding variables = more likely so causal relationships are more difficult to establish - if deception is used, participants cannot give informed consent
27
natural experiment- evaluation
strengths - provide opportunities for research that may not be undertaken for practical or ethical reasons - high external validity- involve the study of real life issues - high ecological validity- less artificial than lab weaknesses - naturally occurring experiments may only happen very rarely- this decreases opportunities for research- also hard to generalise - difficult to establish causal relationships- IV is not directly manipulated and confounding variables are likely - deception is often used, making informed consent difficult confidentiality may be compromised if community = identifiable
28
quasi experiment- evaluation
strengths - often conducted under controlled conditions - higher ecological validity than lab- research less artificial weaknesses - no control over participant allocation to each condition so confounding variables e.g. where they live may effect results - hard to establish causal relationships because IV is not directly manipulated
29
population
a group of people who are the focus of the researcher's interest, from which a smaller sample is drawn
30
in types of experiment, consider
control of variables/ conditions participant variables validity; ecological, internal, external generalisability demand characteristics deception - consent causal relationships replication
31
sample
a group of people who take part in a research investigation the sample is drawn from a target population and are representative
32
types of sampling + definitions
random sampling: every member of the target group has an equal chance of being selected e.g. random number generator opportunity sampling: samples with whoever is available and willing volunteer sampling: people actively volunteer by responding to a request systematic sampling: every nth name from a sampling frame stratified sampling: all the important subgroups are identified and a proportionate number of each are randomly obtained from each strata
33
random sampling- evaluation
strengths - free from researcher and volunteer bias so more likely to be representative weaknesses - does not guarantee a representative sample- some majority subgroups may not be selected - if the group is particularly large, assigning people numbers may be especially time consuming - selected participants may refuse to take part- leads to opportunity sampling
34
opportunity sampling- evaluation
strengths - quick and practical weaknesses - unlikely to be representative of target population due to researcher and volunteer bias - also difficult to generalise the findings- the sample is taken from a specific area
35
volunteer sampling- evaluation
strengths - quick, easy, cheap - a lot of people may respond to the advert, increasing sample size = more accurate weaknesses - volunteer bias so sample is unlikely to be representative of target population a volunteer is a certain type of person- so hard to generalise
36
systematic sampling- evaluation
strengths - simple and effective - no researcher/volunteer bias - more likely to be representative than e.g. volunteer or random weaknesses - subgroups may be missed - not representative if pattern used for samples coincides with pattern in population
37
stratified sampling- evaluation
strengths - produces a representative sample with no bias- so possible to generalise weaknesses - expensive and time consuming - important subgroups may still be missed - can be difficult to identify traits and characteristics to properly stratify
38
in sampling, consider:
representative bias (researcher/ volunteer) generalisable cheap/ practical equal chance of being chosen?
39
why are there ethical issues in psychology
ethical issues arise when a conflict exists between the rights of participants and the goal of research- to produce authentic, valid, worthwhile data- so the correct rules of conduct are necessary
40
who publishes ethical guidelines for research
BPS
41
what are 6 ethical issues in psychology
informed consent deception protection from harm debriefing confidentiality right to withdraw
42
what should be in a consent form
purposes of study, aims the conditions, what the study involves the duration of study the right to withdraw protection from harm
43
difficulties with obtaining informed consent
children under 16 need parental consent mentally unwell people cannot give informed consent, but doctors and family members can on their behalf.
44
alternatives of getting consent
presumptive consent rather than obtaining from participants, a similar group of ppl = asked if a study is acceptable- if this group agrees, consent = 'presumed' prior general consent: participants give permission to take part in a number of different studies, including ones with deception retrospective consent: asking for consent during debriefing
45
deception - why use it, why is it good, what is the problem with it
BPS: if participants have been deceived, they have not given informed consent deception usually avoids demand characteristics- increases internal validity BPS: deception is only acceptable if there is a strong scientific justification- and there is no alternative procedure nb- the severity of deception can differ between studies
46
protection from harm
BPS: the risk of harm should be no greater than they would face in normal life minimise distress inc. feelings of inadequacy, stress minimise long term effecrs i.e. no frightening, endangering, offending no permanent -ve impact can receive counselling right to withdraw @ any point
47
debriefing
return the participants to the state they were prior to the research this is especially important if deception is used the researcher must fully explain the research and results. and answer any questions participant has right to withdraw
48
confidentiality
no participants should be identifiable from reports data collected must be confidential participants must be informed if data is not completely anonymous includes the right to privacy of where the experiment took place
49
right to withdraw
participants can leave at any time, can withdraw their data
50
problems with ethics in psychology
even when guidelines are followed, it is difficult to asses effects like psychological harm, or justify the use of deception deciding whether the ends justify the means is not easy
51
animal rights
- animal research has provided valuable information for psych and medicine - some believe it is ethically wrong to inflict harm and suffering on animals- they cannot give consent - some believe it is cruel to experiment on animals with similar intelligence to humans - animal research could be reserved for less developed animals, but they are then so different from humans that this becomes too difficult to generalise
52
self report
any type of data that involves the participants reporting their own perspectives
53
interview
researcher directly asks the participant questions
54
structured interview + evaluation
fixed set of questions that are the same for all participants strength - like questionnaires, straightforward to replicate due to standardised format, also minimises differences between interviewers weakness - not possible to elaborate on points so limited information is collected
55
unstructured interview + evaluation
there may be discussion topics but it is less constrained- can elaborate strength - much more flexibility than structured- can gain a more well rounded view weakness - analysis of data is more complex, drawing conclusions is more difficult
56
semi-structured interview + evaluation
set questions but follow up questions can be asked strengths - like questionnaires, straightforward to replicate due to standardised format, also minimises differences between interviewers - much more flexibility than structured- can gain a more well rounded view weaknesses - analysis of data is more complex, drawing conclusions is more difficult
57
interview- evaluation
strengths - rich data: detailed information, fewer constraints than questionnaires - useful in pilot studies- easy way to obtain data - unlike observations, can access people's thoughts and feelings that cannot be seen but can be asked about - unlike questionnaires, can clarify what qs mean, increasing validity weaknesses - self report: unreliable, effected by social desirability bias - impractical: time consuming, requires skilled researchers - analysing lots of qualitative data is hard - relies on people being able to explain their thoughts and feelings
58
thematic analysis
analysing qualitative data by identifying patterns in material (not pre-determined categories)
59
content analysis
analysing qualitative data using coding units e.g. themes create checklist of relevant categories- tally behaviours
60
questionnaires + what to consider
participant given a set of pre-set questions they must respond to to consider 1. type of data: qualitative/ quantitative - open qs: reply in any way and in detail- hard to analyse - closed qs: limit the answers that can be given- less detail but easier to analyse 2. ambiguity: avoid question and answer options that are not clearly defined 3. double barreled questions: participants may wish to answer differently for each part 4. leading questions: may lead ppt to particular answer 5. complexity: use clear English, avoid jargon
61
questionnaires- evaluation
strengths - practical: can collect lots of data quickly and cheaply - can be completed without researcher present - can make comparisons easily - participants more willing to answer honestly bc. anonymous - decreases investigator effects- reactions not visible weaknesses - leading questions - biased samples- some people are more likely to respond so unrepresentative sample - self-report- social desirability bias - ethics- confidentiality around sensitive topics = problem
62
acquiescence bias
the tendency to agree with items on a questionnaire, regardless of the contents of the questions
63
designing questionnaires- scales/ choice options
likert scale: strongly agree --> strongly disagress rating scales: 1--> 5 fixed choice options: choose applicable from list
64
in self-report, consider:
amount/ quality of information bias (social desirability, volunteer, researcher, acquiescence) validity (clarifying answers) practical / ease of analysis
65
validity
how well a test measures what it claims to
66
reliability
how consistent and dependable a test is
67
the Hawthorne effect
someone interested in what they're doing and the attention they are receiving from researchers- they show more positive responses - results may be artificially high
68
social desirability bias
people try to show themselves in the best possible light to make them appear socially acceptable
69
researcher bias
researcher's expectations influence how they design, measure and analyse and the questions they ask
70
investigator effects
anything the researcher does to affect the behaviour of the participant- could lead to demand characteristics
71
correlation
the measure of the relationship between two co-variables
72
correlation co-efficient
number from -1 to 1, shows how closely to variables are linked
73
3 types of distribution curves
normal: symmetrical, mean=median=mode, width depends on S.D positive: cluster at lower end, tail on right, modemedian>mean
74
correlation studies- evaluation
strengths - variables can be studied that would be unethical to manipulate - gives ideas for future research - can be used to test for reliability and validity weaknesses - correlation does not mean causation, only link - 3rd variable may be responsible- controlled conditions are necessary
75
naturalistic observation + evaluation
observing subjects in their natural environment- no interference with subjects strengths - ecological validity- no demand characteristics, natural behaviour increases validity - theory development- can develop ideas about behaviour that could later be tested in more controlled conditions weaknesses: - EV- cannot be controlled, so replication and generalisability decreases - observer bias-expectations may influence what they focus on and record - ethics- must respect privacy, only occur where people would expect to be observed
76
controlled observation + evaluation
carried out in an environment set up by the researcher, managing variables strengths - variables are more controlled, EV minimised and cause-and-effect easier to establish - replication = easier and reliability easier to establish weaknesses -lower ecological validity -demand characteristics- ppts aware they're observed.
77
participant observation + evaluation
researcher participates in activity under study strengths - develops a relationship with group- greater understanding may increase validity weaknesses - may lose objectivity by building relationships- may identify with some more than others - participants may change behaviour if they know there is a researcher among them
78
non-participant observation
observes behaviour, but not involved with group strength - objective, does not develop bias weakness - not part of group dynamic, may decrease understanding/ validity
79
participant and non participant observation can be overt/ covert evaluate both
overt: researcher's presence = obvious strength - much more ethically sound weakness - demand characteristics- change behaviour covert: researcher's presence = unknown strength - demand characteristics minimised so validity increased weakness - ethical approval = difficult
80
recording data: unstructured observation structured observation written notes video/audio recordings
unstructured observation: writing down everything you see - rich in detail - useful in small scale observation w/ few ppts structured observation: behaviour categories pre-defined - easy to gather relevant data - BUT may miss something significant written notes- useful for qualitative data video/audio: more accurate, permanent record
81
categorising behaviour
operationalise what you intend to observe- how it will be measured behavioural categories as checklist- observable, measurable, self-evident observations therefore objective, clear focus, increases reliability, easy to analyse
82
sampling behaviour unstructured / structured (+types of structured)
unstructured: continuous recording of behaviour structured: systematic method of sampling observations - event sampling, time sampling
83
event sampling + evaluation
only record particular events that you are interested in strength - focus exactly on specific behaviours weakness - interesting behaviours could be ignores if there are many complex behaviours occurring at one time
84
time sampling
if behaviours occur over a long period, they may be recorded at set time intervals - chosen randomly strength - convenient to carry out - avoids researcher bias weaknesses - interesting behaviours outside time samples are not recorded so recorded behaviours are unrepresentative of samples as a whole
85
pilot studies + uses
small scale version of an investigation- takes place before real investigation - checks that procedures, materials, measuring scales work- changes can be made - checks that questionnaires/interviews= worded in unambiguous manner - in observational studies, good way to check coding systems before irl observation
86
trials single/double blind, placebo, control
single blind: only the researcher knows what conditions participants are in - control for demand characteristics double blind: neither the participant nor researcher know who is in what conditions- control for observer bias + demand characteristics placebo: can be used to check the condition being tested is actually having an effect control: used for comparison if the change in behaviour of the experimental group is significantly greater than the control group, the researcher concludes that the cause of this effect = due to manipulation of IV, assuming confounding variables = constant
87
peer review + main aims
aspects of the investigation being scrutinised by a small group of experts in that field main aims 1. allocate research funding to proposed research project 2. validate quality and relevance of research + accuracy of hypotheses, methodology and conclusions 3. suggest amendments/ may suggest minor revisions orb that it is completely inappropriate
88
peer review evaluation
strengths - minimises bias therefore: establishes accuracy and validity makes research more statistically significant promotes the scientific process weaknesses - anonymity some reviews may use their anonymity as a way of critiscising rival researchers- many researchers are in competition for limited research funding some journals favour 'open reviewing' where names are public for this reason - publication bias editors want to publish significant, headline- grabbing findings to increase credibility and circulation also prefer to publish positive results- this can lead to the 'file in drawer' effect selective publishing creates a false impression of current state of psychology - burying ground breaking research peer review process may want to maintain the status quo within particular scientific fields because reviews are likely long-established researchers, they are perhaps more favourable to research that matches their own view so new innovative research is more likely to be discarded therefore, peer review may slow the rate of change within a dicipline
89
validity - face internal external temporal ecological concurrent
face validity: the degree to which a procedure appears effective in terms of its stated aims internal validity: whether results obtained are solely effected by changes in the variable being manipulated in a cause-and-effect relationship external validity: whether data can be generalised to other situations outside the research environment. temporal validity: research findings successfully apply across time ecological validity: data collected is generalisable to the real world based on the conditions the research is conducted under. concurrent validity: whether the test produces the same results as another established measure.
90
qualitative data + evaluation
expresses thoughts and feelings in a non-numerical way strengths - broader in scope - ppt can develop their opinions - greater external validity- provides researcher with more meaningful insight weaknesses - difficult to analyse- to see patterns + make comparisons - conclusions therefore rely on the subjective interpretation of the researcher
91
quantitative data + evaluation
data that can be counted numerically strengths - simple to analyse and draw conclusions - data in numerical form is more objective and less open to bias weakness - narrower in scope and meaning than qualitative fails to represent real life
92
primary data + examples + evaluation
'field research'- original data, collected specifically for the purpose of the investigations by the researcher - arrives first hand from participants can be gathered by experimenter e.g. questionnaire, observation, interview strength - carefully controlled procedures and operationalised variables weakness - expensive to obtain
93
secondary data + examples + evaluation
'desk research' - data that has been collected by someone other than the researcher- it already exists - has often already been subjected to statistical testing can be gathered from journals, books, websites strength - easier to conduct- a bulk of research has already been carried out weakness - higher chance of researcher bias- can choose what data to use
94
meta analysis + evaluation
results from many different studies brought together to formulate a conclusion strength - decreases the problem of obtaining large sample size weakness - difficult to formulate conclusions from many conflicting results
95
case studies + evaluation
- an in-depth study of one person, group or event - nearly every aspect of the subject's life and history is analysed to seek patterns and causes of behaviour - usually carried out in the real world - idiographic, individualistic strength - lots of qualitative data gathered over time - depth of analysis increases validity - may stimulate new paths for research weaknesses - low control over EV- difficult to establish cause + effect - poor reliability and replication - hard to generalise due to unique situation - retrospective data may not be as accurate or relevant- difficult to verify