Reasearch Methods Flashcards
1
Q
What is an aim?
A
Outline research topic
- always start aims with “to investigate”
2
Q
Alternative hypothesis
A
- prediction
- could be directional (one tailed)cor non directional (two tailed)
3
Q
Directional hypothesis
A
States which way they predict the results will go
E.g “boys will score higher on the maths test than girls”
- good if there’s previous data
4
Q
Non directional hypothesis
A
States there will be a difference but not what the difference will be
E.g “there will be a difference in maths test scores between boys and girls”
5
Q
Null hypothesis
A
This hypothesis is accepted if the results of experiment are not significant
- states there will be no difference of any difference is down to chance
6
Q
Independent variable
A
The thing that is manipulated/ changed
E.g the different groups, different conditions
7
Q
Dependent variable
A
The thing that is measured
- this doesn’t change
8
Q
Operationalise
A
Explaining how the variables could be manipulated/ measured
9
Q
Correlational hypothesis
A
- in a correlation there is no IV and DV
- there are co variables- two things which are measured and cleared for a relationship
E.g “there will be a positive correlation between footsize and height”
10
Q
Random sampling
A
Each participant has an equal change of being selected
E.g random name generator, name drawn from a hat
11
Q
Opportunity sample
A
Asking people who are available at that time to take part
E.g researcher may ask parents picking their children up from school
12
Q
Volunteer sample
A
Researcher advertises the study and people who see the advert may get in contact and volunteer
E.g poster and newspaper
13
Q
Systematic sampling
A
Selecting every nth name from a list
14
Q
Stratified sampling
A
Selecting people from every portion of your population
- in the same proportions
15
Q
Opportunity advantages and disadvantages
A
A: easy to do, not time consuming
D: tend to get similar volunteers take part
16
Q
Random advantages and disadvantages
A
A: fairest technique- equal way to pick people
D: Difficult to achieve, time consuming, effort
17
Q
Systematic advantages and disadvantages
A
A: provided representative sample
D: it is researcher bias
18
Q
Stratified advantages and disadvantages
A
A: good for clear representation
D: complicated to do, time consuming
19
Q
Volunteer sampling
A
A: easy to do, not time consuming, minimal input from researcher
D: tend to get very similar volunteers take part- not generalisable
20
Q
What is an experiment?
A
- involves a change in an independent variable
- researcher will record or measure the effects of this on dependent variable
- how the iv is manipulated and under what circumstances varies with the type of experiment
21
Q
Laboratory experiment
A
- controlled artificial environment
- independent variable is manipulated
- participants are randomly assigned to conditions
22
Q
Field experiment
A
- natural environment
- independent variable is manipulated
- a “true” experiment
23
Q
Natural experiment
A
- independent variable is not manipulated
- it is unplanned and has occurred because of a naturally occurring event
- could be natural or controlled setting
24
Q
Laboratory advantages and disadvantages
A
A: easily replicated, has internal validity
D: could lack external validity, artificial setting
25
Field advantages and disadvantages
A: not an artificial setting- more external validity, demand characteristics are lower
D: can’t control for some extraneous variables, ethical issues- no informed consent (covert experiments)
26
Natural advantages and disadvantages
A: it is ethical
D: participants may not be randomly allocated to experimental conditions, not easy to replicate
27
Quasi experiment
- independent variable is not manipulated- it is based on an existing difference between people e.g age, gender, personality
- there is planned manipulation of this naturally occurring IV
- could be natural or controlled setting
28
Quasi advantages and disadvantages
A: easily replicated- under controlled lab conditions
D: can’t randomly allocate participants
29
Self report methods
Both questionnaires and interviews are types of self report methods.
This is because the participant reports their own thoughts and feelings about a particular matter
30
Open question
The participant can give any answer they wish
31
Closed question
There are a set number of responses which participant selects from
32
Questionnaire
A self report method with written questions which the participants selects from
33
Fixed choice option (closed question)
Includes a lot of possible optional and respondent are required to indicate what applies to them
34
Likert scale (closed questions)
The respondent indicates their agreement with an statement scale (ranging from strongly agree to strongly disagree)
35
Rating scales
Participants select a value that represents their strengths of feeling about a particular topic
36
disadvantages questionnaires
- double barrelled questions contains 2 questions in one (only may agree with one half but not the other)
- if it is too lengthy, people are less likely to finish it
- leasing questions- the phrasing of the question indicates a particular response
- biased options- obvious as to what option leads to what conclusion
37
Conducting an observation- behavioural categories
- these are used in structured observations as a checklist
| - the target behaviour is broken down into behavioural categories and then operationalised
38
Sampling methods- continuous recording
- all instances of target behaviour are recorded
| - in complex observations this is not always feasible
39
Sampling methods- event sampling
Counting the number of times a particular behaviour occurs in a father individual or group, doesn’t take account time- just a tally
40
Sampling methods- time sampling
Recording behaviour within a lee established time frame
| E.g take note what a target individual is doing every 30 seconds of some other time interval
41
Structured interviews
- face to face or phone
- contain standardised pre set questions
- sometimes includes a list of pre determined answers
42
Unstructured interviews
- a conversation
- the interviewer has a general idea of the topics they want to discuss but the actual questions and sequence of questions develop during the course of the interview
43
Semi structured interviews
- still has a list of issues/ questions
- however, questions can be asked in any order
- if something interesting comes up the interviewer can veer away from standardised questions
- questions generally open- ended but data can also be collected
44
Naturalistic observation
A research method carried out in a naturalistic setting, in which the investigator does not interfere in any way but merely observed the behaviour in question
45
Controlled observation
Observing behaviour under controlled conditions
46
Overt observations
The participants are aware That they are being observed
47
Covert observation
The participants are not aware they they are being observed
48
Structured observation
Researcher determines precisely what behaviours are to be observed and used a standardised checklist to record the frequency with which they are observed within a specific time frame
49
Unstructured observation
The observer recalls all relevant behaviour but has no system
50
Participant observation
The researcher gets involved with participant activity so they can experience it for themselves, joins in
51
Non participants
The observer remains separate from the participants to maintain objectivity
52
Overt observation: strengths and weaknesses
S: ethical- they have consent
W: Hawthorne effect- act differently when aware of being watched
53
Covert observation: strengths and weaknesses
S: no Hawthorne effect
W: not ethical (no informed consent)
54
Structured
S: easy to replicate
W: cant use new behaviours- not standardised checklist
55
Unstructured observation: strengths and weaknesses
S: record all behaviour- including unexpected
W: ignore unexpected behaviour
56
Controlled observation: strengths and weaknesses
S: can control extraneous variables
W: less generalisable to real life, low internal validity
57
Naturalistic observation: strengths and weaknesses
S: good external validity
W: small scale- less representative
58
Participant observation: strengths and weaknesses
S: high validity- better insights
| W: researcher may come to identify too strongly with those they are studying and lose objectivity
59
Non participant: strengths and weaknesses
S: more objective
W: thoughts + feelings lost
60
Behavioural categories: strengths and weaknesses
S: makes data collection more structured and objective
W: there can’t be a ‘dustbin category’ in which the researcher finds other behaviours outside the categories
61
Event sampling : strengths and weaknesses
S: useful when the target behaviour or event happens quite infrequently
W: too complex- observer may overlook important details
62
Time sampling : strengths and weaknesses
S: this is useful if you have a lot of behaviours you need to record
W: data can lack detail if every behaviour isn’t noted
63
What is a correlation?
When two things are measured in order to identify if there is a relationship between them
64
Positive correlation
Both variables increase together
65
Negative correlation
As one variable increases, the other decreases
66
No correlation
No relationship between the variables
67
Curvilinear
The relationship is predictive although it is not linear but curved
68
Intervening variable
A variable that comes between two other variables, which is used to explain the association between those two variables
69
Continuous variable
A variable that can take long on any value within a certain range
70
Correlation co- efficient
- Number between 0 and 1
- Tell us how strong the correlation is- the nearer to 1 the stronger the correlation
- It has the sign in front of the number which tells us whether the correlation is positive or negative
71
Correlation or experiment?
- In an experiment the researcher controls or manipulates the independent variable
- in contrast, in a correlation there is no manipulation of the two variables
- it is therefore not possible to determine cause and effect
72
Types of experimental design: independent groups
A separate group of participants for each condition of the IV
E.g IV gender- one group is male and the other is female
73
Types of experimental design: matched pairs
A separate group of participants for each condition of the IV but they are fitted for certain characteristics
E.g IV gender= separate group of males and females but I will make sure that the groups are matched for age and income
74
Types of experimental design: Repeated measures
Every participant completes all conditions
E.g one group has music playing then the same group does another test without music
75
Independent groups: advantages and disadvantages
A: no demand characteristics, no order effect
D: can’t establish cause and effect, individual differences
76
Repeated measures : advantages and disadvantages
A: less differences- no individual differences, more valid
D: increase in demand characteristics, order effect- they could get better, they could get bored or tired
77
Matched pairs : advantages and disadvantages
A: only take part in a single conditions- reduces demand characteristics
D: matching can be time consuming and expensive
78
Pilot studies
- conducted to test design
- it is also conducted to test measures used
- can be used to test for reliability to re test and yes
- used to identify extraneous variables so controls can be put in place for the actual study
- used to ensure all the ethical issues have been dealt with
79
What is meant by ethics?
The consideration of what is acceptable or right behaviour in the pursuit of a personal or scientific goal
80
Informed consent
The participant has been informed about everything that Is going to happen in the experiment
- full knowledge, no deception
81
Right to withdraw
Allowing the participant to stop the experiment
| They can also withdraw their data
82
Deception
When the participants don’t know what is actually going on in the experiment
- researcher is lying
83
Confidentiality
Giving away personal information e.g name
| Data kept in confidence
84
Protection of participants
Not harming the participants emotionally or physically
85
Dealing with informed consent
- participants should be issued with a consent letter or form detailing all relevant information
- it is then signed if participant wants to take out experiment
86
Alternatives ways of getting consent: presumptive consent
Rather than getting consent from participants themselves, similar group of people are asked if the study is acceptable
87
Alternatives ways of getting consent: prior general consent
Participants give their permission to take part in number of different studies- including one that involved deception. By consenting, participants are effectively consenting to be deceived
88
Alternatives ways of getting consent: retrospective consent
Participants are asked for their consent having taken part in the study. May not be aware of their participation
89
Internal validity
Affected if there are extraneous or cofounding variables- this is lowered because then we are no longer testing the effect of the IV and DV
90
Extraneous variable
Which affect the DV but don’t vary systematically with the IV
(Random error- might not affect everyone in the same way)
E.g temperature or room
91
Confounding variables
Affect the DV and do vary systematically with the IV (affects everyone in the same way)
92
External validity
Can we accurately generalise?
Population validity- is our sample representative?
Ecological validity- is the environment accurate to real life?
Temperal validity- is the experiment still accurate to today’s validity over time society?
93
Demand characteristics
Type of extraneous variable
Difficult to control
Participants may guess the aims of the research and then may act in a way that they think is expected
94
Investigator effects
Unwanted influence of the researcher on the experiment
| This may be unconscious behaviour, such as smiling more with one condition compared to another
95
Participant reactivity: Hawthorne effect
When the added attention of being in a story affects participant behaviour
96
Participant reactivity: demand characteristics
When participants think they have figured out the aims as the experiment and change their behaviour
97
Participant reactivity: social desirability
When participants try to look good by answering/ behaving in a socially acceptable way
98
Investigator effects: experimenter bias
When the experimenter effects the results
| E.g through their interpretation, through body language
99
Investigator effects: interviewer bias
When the interviewer affects the responses of the interviewee
100
Investigator effects: greenspoon effect
When the interviewer makes affirmative noises e.g mmhhhmm
| After certain answers, this affects the way the participant responds
101
Randomisation
Using chance at every available opportunity
| Controls for experimenter bias
102
Counterbalancing
Half of the participants do condition one, the other half do condition two then they swap
103
Single blind design
Use of deception to mislead participants
| Controls for demand characteristics
104
Standardisation
Keeping everything the same for every participant
| Controls for experimenter bias
105
Double blind design
When both the researcher and participant don’t know the aims of the study
Controls for demand characteristics and experimenter bias
106
Reliability
- consistency
- if they did the test on another day would they get the same results?
- if there is standardised procedures and instructions
I.e is there consistency in the way the experiment is conducted
107
Inter- rated reliability
- are the observers scoring in the same way?
- more than one researcher looking at the investigation
- testing for consistency
- check how well they link
108
Checking for reliability
- conduct the test again and see if you get the same results
- conduct and spearmens rho test comparing the scores- testing for a correlation (if there is no correlation between the observers etc, then it is not consistent so not reliable)
109
Improving reliability
- observers familiarise themselves with behavioural categories
- conduct a small scale pilot study
- compared the data observers have gotten by calculating a correlation co efficient
- operationalise variables if needed
- repeat
110
Purpose of review
1) Validate the quality and relevance of research
2) Suggest amendments and improvements
3) Allocation of research funding
111
Process of peer review
- other psychologists check reports
- psychologists working in similar field
things considered: validity, significance, originality, methods, design
- report can be accepted, amendments, suggested or rejection
112
Strengths of peer review
- Essential so that high quality is produced
| - Keeps a check on dishonest psychologists
113
Weaknesses of peer review
- Publication
- Expensive
- Time consuming
- Subjective
114
Qualitative data
Expressed in words, non numerical
115
Quantitative data
Expressed numerically rather than in words
116
Primary data
First hand from participants, collected specifically for the purposes of the research
117
Secondary data
Data collected by someone other than the person doing the research
118
Quantitative data strengths and weaknesses
S: simple and quick- easy to analyse, use measure of central tendencies
W: less in depth opinions
119
Qualitative strengths and weaknesses
S: more in depth research and opinions, greater external validity
W: could be time consuming, harder to analyse, reply on subjective interpretations, subject to bias
120
Primary data strengths and weaknesses
S: you have control, authentic data, you know it is accurate
W: time consuming- may be hard to achieve and expensive
121
Secondary data strengths and weaknesses
S: easier to get- quicker and cheaper, been peer reviewed- increase in validity
W: May be inaccurate, could be out of date
122
Measures of central tendency
Find the average
Mean= sum of all scores divided by the number of values there are
Mode= most common value
Median= middle value
123
Measures of dispersion
Find the spread/ variety of data
Range= highest value- lowest value
Standard deviation= calculates how far scores deviate from the mean
124
Mean strengths and weaknesses
S: includes all data, most representative
W: could be anomalies (skews data) , could be time consuming
125
Mode strengths and weaknesses
S: can be used with qualitative data, not affected by extreme values
W: useless if there is no mode, mode may not be representative
126
Median strengths and weaknesses
S: not affected by extreme values, can be used when data is not internal
W: isn’t representative of the data as a whole
127
Range strengths and weaknesses
S: includes all data pieces
W: only takes account two extreme values, anomalies can be easily affected
128
Standard deviation strengths and weaknesses
S: all of the data is included in calculation so is more representative of the data as a whole
W: is affected by extreme values
129
What are inferential statistics?
- draw conclusions about our data
- tell us whether our results are significant enough that we can generalise with any certainty
- based around probability
130
Significance (sign test)
- if a sign test shows our results are significant we accept our alternative hypothesis
- if they are no significant we accept our null hypothesis
