Research Methods Flashcards
1
Q
Self-report Technique
A
A method where people state or explain their own thoughts/feelings that relate to a given topic
2
Q
Social-desirability bias
A
Participants fail to report social undesirable behaviours to appear more likeable
3
Q
Demand Characteristics
A
Participants subconsciously change answers after forming idea of what experiment may be about
4
Q
Response Bias
A
Responses are biased due to another external factor
5
Q
Acquiescence bias
A
Individuals are likely to agree with something regardless of how they feel, and agree with the survey questions rather than own thoughts
6
Q
Qualitative data
A
Language based data collection expressed through words, non-numerical
7
Q
Quantitative data
A
Numerical data that can be statistically analysed
8
Q
Open questions
A
Can add detail to it
More information can be given
Cannot be compared easily
9
Q
Closed questions
A
Comparable data
Can’t easily find out extra information, have to follow a script
10
Q
Interviews
A
Effort from researcher
Can see the participant and gauge responses
11
Q
Structured interview
A
Can be replicated
Standardised, reduced difference between interviewers
Can’t deviate from the topic or explain questions: limits amount of data collected
12
Q
Unstructured interview
A
More flexible
Follow up points as they arise
Unexpected information
Interviewer bias
Not easy to analyse the data given
Irrelevant information may be given
Lying for sake of being liked: however, rapport should be built so there are truthful responses given
13
Q
Semi-structured interview
A
Follow up questions can be asked
Not easy to compare the data given as different questions asked
Some data can be compared on the questions in common between interviewees
14
Q
Questionnaires
A
Cost effective
Large amounts of data collected
Researcher doesn’t need to be present (effort involved is reduced)
Straightforward to analyse
Statistical analysis, comparisons can be made easily
Graphs and charts
May not always be truthful, want to present in positive light (underestimating frequency, for example)
15
Q
Likert Scale
A
Respondent indicates agreement with a statement using a scale ranging from Strongly Agree to Strongly Disagree, for example.
16
Q
Rating Scale
A
Works in a similar way, but participants identify a value that represents their strength of feeling about a topic (e.g entertaining to not at all entertaining
17
Q
Fixed-choice option
A
Includes a list of possible options, and the respondents indicate which of these options apply to them
18
Q
Interview Schedule
A
The list of questions that the interviewer wants to cover, and is standardised to avoid interviewer bias
19
Q
Interview bias
A
The expectations or opinions of the interviewer interferes with the judgment of the interviewee
20
Q
Leading question
A
Question that guides a respondent to a particular answer (e.g ‘Is it obvious that…’)
21
Q
Emotive Language
A
Emotive words stir a response in people. Need to be avoided, and neutral words should be used instead of accusing people of things, as this can affect the responses of the participant
22
Q
Double-Barreled questions
A
Two questions in one, participants may agree with one half of the question, and not with the other.
23
Q
Randomisation
A
Researchers can reduce experimenter effects by using random chance in the design of their experiments.
E.g the order in which words are presented in a memory test are set by chance, rather than the experimenters choice
24
Q
Standardisation
A
As far as practically possible, researchers try to ensure all participants have the same experience in the experiment (E.g same place, same time, same test equipment, same interviewer, same questions, same measures of behaviour)
Makes a measure of behaviour RELIABLE (consistent)
25
Reliability
A measure of whether something stays the same, i.e. is consistent. The results of psychological investigations are said to be reliable if they are similar each time they are carried out using the same design, procedures and measurements
26
Validity
Whether a measure actually measures what it claims to be measuring, and is true or legitimate
27
Independent groups/measures
Participants are allocated to either one group or another, and are exposed to different experimental conditions
28
Repeated measures
The same subjects participate in all conditions of the independent variable
29
Matched pairs
Overcomes issue of participant variables, matching is done according to a relevant characteristic which might affect behaviour in the study, matches someone in the other condition. Matches may be based on age, gender, skill level, personality, educational attainment etc.
30
Evaluation of matched pairs
Strengths:
-Can reduce participant variables in an independent groups design
Limitations:
-Matching will never be perfect, even identical twins have differences in attitudes and behaviours
-Process of matching is time consuming
-Pre-testing becomes necessary
-May not be possible within budget
31
Random allocation
Rather than the researcher deciding who goes in which groups, participants are allocated to each group by random chance
32
Researcher bias
The beliefs or expectations of the researcher influence the research design or data collection process. Can also be caused by leading questions or emotive language
33
Counterbalancing
-Improvement to be made to repeated measures design
-Half participants do condition A, followed by B.
-Other half do condition B followed by A, and so distribues order effects (tiredness, practice) across both conditions
34
Evaluation of random allocation
-Can't guarantee removal of confounding variables
-Random allocation removes researcher bias from independent measures, but participants in each condition may still be different by chance
35
Evaluation of Counterbalancing
-Can't guarantee removal of confounding variables
-Counterbalancing (ABBA), shares out the effect of fatigue or practice across both conditions
-But they are not removed from the experiment
36
What is discrete data and how it is presented?
If data is made of whole numbers that are counted and not measured, e.g 3 children, 100 workers.
Presented using a bar chart
37
What is continuous data and how is it presented?
If data is measurable and can take on any value, e.g 3.25kg
Presented through histograms or line graphs
38
Positively skewed graph
Most scores are at the left of the graph
Long tail on the right
Mode = at the highest point of the peak
Median = next highest
Mean = dragged along to the right
E.g a difficult test in which most students get low marks, and a few get very high marks.
39
Negatively skewed graph
Most distribution is at the right of the graph
Long tail on the left
Mode = at the highest point of the peak
Median = next
Mean = dragged along to the left
E.g an easy test in which most students get high marks and a few students get very low marks
40
Bar charts
A type of graph in which the frequency of each variable is represented by the height of the bars
Used when data is divided into categories (discrete data)
Bars do not touch, separated to show a difference in conditions
41
Histograms
A type of graph which shows frequency but, unlike a bar chart, the area of the bars (not just the height) represents frequency.
The x axis must start at a true zero, and the scale is continuous
Bars are touching, showing continuous data rather than discrete
42
Scattergrams
A type of graph that represents the strength and direction of the relationship between covariables in a correlational analysis
Do not depict differences but instead depict correlations and associations between co-variables
43
Line graphs
Represent continuous data
Points are connected with lines to show change in value
44
What is content analysis?
A type of observational research technique in which people are studied indirectly via the communications they produce.
It is a technique for systematically analysing qualitative information.
It involves drawing up coding categories and counting how often these categories occur.
It converts qualitative data into quantitative data
45
How is content analysis carried out?
Primary data (unstructured interviews, open questions, unstructured observations)
Secondary data (newspapers, magazines, television adverts, movies, facebook posts, journals texts and graffiti)
46
Thematic analysis
Similar to a content analysis, the material to be analysed might be any qualitative primary data such as unstructured interview transcripts or secondary data, e.g: diary, TV advertisements, or interview transcripts.
Themes identified are likely to be more descriptive than the coding units in a content analysis.
The themes are not turned into quantitative data.
Once the researcher is satisfied that the themes they have developed cover most aspects of the data adequately, they may review other, similar data to test the validity of these themes.
They may then write up a final report, typically using quotes from the data to illustrate each theme.
47
Strengths of Content/Thematic analysis
Content/Thematic analysis are both easy techniques to use and help to summarise qualitative information.
They get around ethical issues of conducting research by using secondary data already in the public domain, so consent can be assumed.
Content analysis allows a statistical analysis to be conducted if required since there is quantitative data as a result of the procedure.
48
Limitations of content/thematic analysis
Content/Thematic analysis merely summarise and describe behaviour; they cannot attribute a cause to that behaviour.
Both Content/Thematic analysis can suffer from subjectivity: when identifying codes/themes the researcher might impose his/her ideas on the content and there is the risk that opinions and motivations are attributed incorrectly.
Content analysis: if the coding units are clearly defined and not open to interpretation, this can be a reliable way of analysing qualitative information as the codes can be applied in the same way over time and with different researchers.
49
What are the four kinds of experiment?
Lab, field, natural and quasi
50
Operationalisation
How a variable is clearly defined by the researcher, and defining concepts
51
Features of a lab experiment
- Takes place in a controlled environment
- IV is controlled/manipulated by researchers
- DV is measured
52
Features of a field experiment
- Takes place in a natural environment
- IV controlled/manipulated by researchers
- DV is measured
53
Features of a natural experiment
- IV is a natural or real world even or condition
- NOT manipulated by researchers
- DV is measured
Note: a natural experiment could take place in a lab, but it is the naturally occuring iV that makes it nature, NOT the environment where participants are being tested
54
Features of a quasi-experiment
- IV is pre existing characteristic (not controlled by researchers)
- DV is measured
55
Evaluations of lab and field experiments
- Lab and field experiments have control over the IV, greater internal validity
- The lab has the greatest degree of control, a field experiment may be affected by random events outside of the researchers control.
56
Evaluation of quasi and natural experiments
- Natural and quasi experiments lack control over the IV BUT they are useful, enabling research into variables which for practical or ethical reasons could not be done in a field/lab experiment
-Eg, would not be practical to invent new technologies, but can compare the behaviour of those who have mobiles with those that don't.
57
What is sampling?
Process of identifying who will take part in the experiment
58
Why is sampling important?
Impractical do to psychology by investigating everyone, and so researchers select a few people for their studies, and then generalise the findings from the sample to the target population
59
Is it okay to generalise from a sample to the whole population?
Yes, BUT the sample and target population should be similar, and so the sample is representative of the target population
60
Random Sampling
Every member of the target population has an equal chance of being chosen
61
Systematic Sampling
Uses a predetermined system to select the participants from a target group
62
Stratified Sampling
Researchers identify subgroups within the target population, and then select a sample with the same sub-group proportions in the target population (ie, representative of age in target population, 10% 18-25 in both population and sample, for example)
63
Opportunity Sampling
Using people who are conveniently available for the investigation
64
Volunteer Sampling
Participants self-select to become part of a study because they volunteer when asked, or respond to an advert
65
What are ethical issues?
Problems faced by psychologists in balancing their needs with the needs of participants. There can be a conflict of interest between the two
66
What are ethical guidelines?
Set out by the British Psychological Society (in Britain) and are the values and standards that psychologists should follow when doing research
67
Informed consent
Potential participants should be told in advance what will happen if they get involved in a psychology investigation
68
Deception
When participants are lied to/not told the full truth about the study.
Deceived participants cannot give fully informed consent
69
Protection from harm
Participants should be physically and psychologically safe, including: not being embarrassed, ridiculed, pressurised, endangered
Must know they can withdraw at any time
70
Privacy and confidentiality
People have a right to privacy with their personal information, but researchers often collect personal information (such as feelings/attitudes/reactions), and such information should be confidential
71
How should privacy be protected for participants by researchers?
Should not to record names/addresses, case studies refer to people by initials, personal data should be stored securely and destroyed once the study is complete, and participants7 are told they can withdraw their data from the study.
72
Presumptive consent
rather than getting consent from participants, a similar group are asked if the study is acceptable. If they agree, the consent of the original participants is assumed.
73
Prior general consent
Participants give permission to take part in a number of studies, one of which involved deception, and by consenting, they are saying they are willing to be decieved.
74
Retrospective consent
Participants are asked for consent having already taken part in the study, and may have not been aware of participation or may have been subject to deception.
75
Naturalistic Observation
Takes place in a setting/context where target behaviour usually occurs. All environmental aspects vary freely.
76
Controlled Observation
Watching and recording behaviour within a structured environment where some variables may be managed, e.g. the set up of the room or who enters and leaves the room and the effect it has on the child.
77
Covert Observation
Participants behaviour is watched and recorded with their knowledge and consent
78
Overt Observation
When participants know their behaviour is being observed and have given their informed consent beforehand
79
Participant Observation
Observer becomes part of group they’re studying
80
Non-participant Observation
When the researcher remains separate from the people they are studying, and records the behaviour in an objective manner
81
Unstructured Observation
Write down everything you see, qualitative data.
82
Structured Observation
Record target behaviours only, quantitative data
83
Behavioural Categories
Precisely defined, observable, measurable
84
Event Sampling
Record every time a behaviour is observed
85
Time Sampling
Record what is happening at set intervals
86
Inter-observer reliability
Measure the level of agreement between observers recording the same behaviour to check consistency
87
Pilot Study
A practise, trial run, to make sure the experimental procedure works as intended. A pilot study could prompt researchers to improve or modify the procedure so they end up with relevant, useful data.
88
Single blind procedure
A way to reduce demand characteristics
Participants are not told the:
-study aim
-that there is a control group
-which experimental condition they are in
89
Double blind procedure
Adds extra level of control to single blind
Researcher who interacts does not know the experimental aim or conditions of the experiment
90
Control group
Use of a second comparison condition
Essential in any experiment
Provides a benchmark and point of comparison
How the IV affects the DV can only be answered by having a control group
91
Case study
An in depth investigation, often of one person, or an event or organisation.
92
Who was Phineas Gage and what relevance does he have to psychology?
Tamping iron passed through head, severed optic nerve
Lucky to servive, doctors took interest in his case, as behaviour and personality changed after accident
Very useful to researchers in early days of brain science
93
Case studies on individuals: why are they conducted? How?
Used when researchers want to learn as much as they can about individuals, usually due to unique or rare behaviour
Assessed in many ways, such as:
-interviews and questionnaires with the person
-standardised tests of behaviours, IQ, personality, mental heath
-Biological assessments, brain injury, genetics, hormone levels
-Interviews with family and friends
Conducted over many months or years
94
Examples of case studies?
KF - memory
Henry Molaison (HM) - memory
Clive Wearing - memory
Phineas Gage - brain damage
Christine Sizemore - multiple personality disorder
Genie - attachment
95
Why was the case study on QEMH hospital and Wayne Jowett conducted? What were the findings?
Medical accidents: death of Wayne Jowett at QEMC, Nottingham. Inquiring into how anti-cancer drug was injected into spine rather than his vein, which resulted in his death.
Case study focused on the hospital
Aiming to discover why mistake happened.
Findings:
Wayne died because drug injected into spine rather than vein
Drug had similar name to another drug in same drug cabinet that WAS injected into the spine
Packaging of drug was modified to make it impossibly to inject into spine
96
What are strengths and weaknesses of case studies?
STRENGTH:
Holistic (opposite of reductionist)
Useful
Stimulates more resarch
WEAKNESS:
Biased
Ungeneralisable
Questionable validity
97
What are descriptive statistics?
Descriptive statistics are used to summarise data into a meaningful way
98
What are inferential statistics?
Used to make a judgement about data, researcher can make conclusions
99
What are the stats tests that are needed at A Level?
Sign test
Spearman's Rho
Pearson's r
Wilcoxon
Mann-Whitney
Related t-test
Unrelated t-test
Chi-Squared test
100
What is the purpose of a stats test?
Enable researchers to judge the probability or likelihood that the data either supports the alternate hypothesis or supports the null hypothesis
101
What is a null hypothesis?
No relationship between the two variables being studied
102
What is the alternate hypothesis?
States that there is a relationship between the two variables being studied
103
What do statistical tests do?
Measure the likelihood that results from a study have occurred by chance
104
Why do psychologists use statistical tests?
Want to see:
-In an experiment: if there is a significant effect of the IV on the DV
-In a correlational study: if there is a significant link between 2 co-variables
-Or, if the results could be due to chance
105
When using statistical tests, why do psychologists have to think about likelihood/probability?
No guarantee that findings from study accurately reflect behaviour in real world.
Always risk of error
106
What are significance levels?
How sure a researcher is that the results found are not accidental
107
When is P <= 0.05 needed to be lower?
In drug/medical trials, and drugs can have significant side effects, so may set a high significant level of P<=0.01
Don't want to wrongly conflude that a new drug is effectlve when people could experience side effects
108
What is the usual level of significance?
P<=0.05
109
What is a type 1 error?
Falsely accepting alternate hypothesis
110
What is a type 2 error?
Falsely accepting the null hypothesis
111
What is calculated value?
All stats test use a formula to assess the data, calculated value simply result of that calculation
(Need to be able to work out for sign test but in all other stats questions, told calculated value in stem)
112
What is critical value?
A number that is used as a benchmark for the calculated value
Comparing calculated and critical values enables researchers to decide whether to accept the alternate or null hypothesis
Some tests require to EXCEED critical value, others require to be LESS THAN critical value
More strict for two tailed tests as make less specific prediction
113
What is a one tailed test?
Directional hypothesis, testing for an effect in ONE DIRECTION (OMGGGGGGG)
114
What is a two tailed test?
Non directional hypothesis, testing for an effect in both directions
Critical values are stricter as make less specific prediction
115
What is a sign test?
The sign test is a method used in interferential statistics to determine whether or not an observed result (from a statistical test) is significant
It is a non-parametric test which means that there is no assumption that the data will follow a normal distribution
It is known as the Sign Test as it is based on the number of plus or minus signs present in the data after the calculations have taken place
116
When to use chi square test?
Test of difference in unrelated design, nominal data
OR
Test of association or correlation of nominal data
117
When to use sign test?
Test of difference in related design with nominal data
118
When to use Mann Whitney test?
Test of difference in unrelated design with ordinal data
119
When to use Wilcoxon test?
Test of difference in related design with ordinal data
120
When to use Spearmans rho test?
Test of association or correlation of ordinal data
121
When to use Unrelated T test?
Test of difference in unrelated design with interval data
122
When to use related T test?
Test of difference in related design with interval data
123
When to use Pearson's r test?
Test of association or correlation of interval data
124
What is nominal data?
Named data, participants in groups, categories
For example happy, sad or anxious
125
What is ordinal data?
Can be ranked in meaningful way, data which is placed into some kind of order or scale
Can be compared in terms or more/less than
126
What are levels of measurement?
Quantitative data can be classified into types or levels of measurement, such as nominal, ordinal and interval
127
What is Spearmans rho?
A test for correlation when data is at least ordinal level
128
What is Pearson's r?
A parametric test for a correlation when data is at least ordinal level
129
What is Wilcoxon test?
A test for a difference between two sets of scores. Data be at least ordinal level using a related design
130
What is Mann-Whitney test?
A test for difference between two sets of scores. Data should be at least ordinal level using an unrelated design
131
What is a related t test?
A parametric test for a difference between two sets of scores, data must be interval level with a related design (repeated measures or matched pairs)
132
What is an unrelated t test?
A parametric test for a difference between two sets of scores. Data must be interval level with an unrelated design (independent groups)
133
What is chi-squared test?
A test for an association (difference or correlation) between two variables/conditions. Data should be nominal level using unrelated (independent) design
134
What is interval data?
Data gathered can be represented on a scale where individual units are precisely defined and equal (time, length, size)
135
How to calculate the critical value for the sign test?
Use N
136
How to calculate the critical value for Wilcoxon?
Use N
137
How to calculate the critical value for the sign Related T test?
Df = N-1
138
How to calculate the critical value for Chi^2?
Df = (R-1) x (C-1)
139
How to calculate the critical value for the Mann Whitney test?
Use intersection of Na and Nb
140
How to calculate the critical value for the unrelated T Test?
Df = (Na + Nb) - 2
141
How to calculate the critical value for Spearman's?
Use N
142
How to calculate the critical value for Pearson's r?
Df = N - 2
143
What sections are usually included in a psychology investigation
Abstract: short summary of research paper
Introduction: Introduces research
Method: how the research was conducted
-Design
-Sampling
-Apparatus/materials
-Procedure
-Ethical considerations
Results: Findings of the research
-Summary
-Descriptive statistics
-Inferential statistics
Discussion: Issues encountered, interprets the study's findings, connects them to previous research, acknowledges limitations, and suggests directions for future research
References: credit other researchers who they have drawn on
Appendices: place for supplementary information that is relevant but not essential to the main argument of the paper
144
What do researchers consider before a study?
Aims
Procedure
Duration
What happens with the data
Risks and mitigations
Right to withdraw
145
What does a debrief include?
True aims
More details on procedure
What happens with the data and the right to withhold.
Offer of counselling/support
146
What should consent forms include?
What will happen
Timing
Point of study
Warning
Reassurances
Data protection
What happens after
