Research Methods Flashcards
1
Q
What is an aim
A
A statement of a study’s purpose
2
Q
What is a hypothesis?
A
Predictions based on theory that are scientifically tested
3
Q
3 types of hypothesis
A
One tailed/directional, two tailed/non-directional and null
4
Q
Directional Hypothesis
A
States the difference between conditions
5
Q
Non directional hypothesis
A
States there will be a difference but doesnt say what the difference will be
6
Q
Null hypothesis
A
There will be NO significant difference between the conditions
7
Q
Independent Variable
A
The variable we’re changing/ manipulating
8
Q
Dependent Variable
A
The variable we’re measuring
9
Q
Control
A
The extent to which any variable is held constant by a researcher.
10
Q
Random allocation
A
Everyone has an equal chance of doing either condition
11
Q
Counterbalancing
A
Half the participants participate in condition A before condition B and vice versa. (overcomes order effects)
12
Q
Randomisation
A
Materials are presented in a random order
13
Q
Standardisation
A
Everything should be as similar as possible for all participants
14
Q
Extraneous variables
A
Variables other than the IV that could influence your results
15
Q
Confounding variables
A
A type of extraneous variable that is related to both the independent and dependent variables
16
Q
Ethical guidelines
A
Standards of behaviour, promoting fairness, protecting rights, and minimising harm.
17
Q
Informed consent
A
Knowing aims and giving your permission to take part in the study
18
Q
Deception
A
Deliberately misleading or withholding information
19
Q
Right to withdraw
A
Being able to leave when desired
20
Q
Confidentiality
A
Details should be kept private
21
Q
Protection from harm
A
No more harm than daily life
22
Q
3 types of experimental design
A
Repeated Measures
Independent groups
Matched pairs
23
Q
Independent Groups
A
There are 2 separate groups of participants. One takes park in Condition A and the other in B
24
Q
Independent Groups A+W
A
Fewer demand characteristics
No order effects
But more participants needed
Individual differences
25
Repeated Measures
One group that takes part in both conditions
26
Repeated Measures A+W
No individual differences as the same person does both conditions
Demand characteristics
Order effects
27
Matched Pairs
Two groups and they are matched into pairs for certain qualities such as age or intelligence. One does Condition A and the other B
28
Matched Pairs A+W
No order effects
Controls for individuals differences
Difficult to match people perfectly
Costly and time consuming
29
Types of experiments
Laboratory
Field
Natural
Quasi
30
Field Experiment
Take place outside of the lab but still manipulates IV
31
Field Experiment A+W
Less Artificial
Avoids participant effects producing more natural behaviour
Less easy to control extraneous variables
Ethical Issues (pps unlikely to know they are being studied)
32
Laboratory Experiment
Controlled artificial environment where IV is manipulated
33
Laboratory Experiment A+W
Controlled environment
Minimises extraneous variables
Artificial environment
Pps may behave differently due to environment
34
What is meant by the term 'double blind'?
Neither the participants or the researchers are aware of the aims of the investigation
35
What is meant by the term 'single blind'?
Participants aren't aware of the condition they are in
Attempts to control for the confounding effects of demand characteristics
36
Natural Experiment
Natural Environment. IV manipulated taking advantage of a naturally occuring event
37
Natural Experiment A+W
High ecological validity
Few ethical issues
Many extraneous variables
Naturally occuring events are infrequent limiting research opportunity
38
Quasi Experiment
The IV is a naturally existing characteristic between people and hasn't been changed by anyone or anything
39
Quasi Experiment A+W
Done in labs so high in control
'Real' problems can be studied
There may be confounding variables meaning we can't say cause and effects
40
What are behavioural categories?
Categories defined by the researcher to observe during the experiment
41
2 types of sampling
Event
Time
42
Event Sampling
Counting the number of times a certain behaviour occurs
43
Time Sampling
Recording behaviours in a given time frame
44
Controlled Observation
When the researcher has some measure of control over the environment
45
Controlled Observation S+W
Control over extraneous variables
Easy to replicate
Can't be applied to real life setting
May be subjective towards what the researcher wants to see
46
Naturalistic Observation
Studying behaviour in a natural setting where everything has been left as it is normally
47
Naturalistic Observation S+W
High ecological validity
Natural Environment- generalised to everyday life
Replication is difficult
Uncontrolled extraneous variables
48
Covert Observation
The participants aren't aware that they are being observed
49
Covert Observation S+W
No demand characteristics
Ethical Issues
50
Overt Observation
The participants are aware that they are being observed
51
Overt Observation S+W
Less ethical issues
Might be demand characteristics as they know they are being watched
52
Participant Observation
The observer acts a part of the group being watched
53
Participant Observation S+W
Experience situation and increases validity
Lose objectivity
Difficulty in recording observations
54
Non-participant Observation
The experimenter does not become part of the group being observed
55
Non-participant Observation S+W
More ethical, more objective
Less insight
Not experiencing the same things
56
Structured Observation
The researcher determines precisely what behaviours are to be observed and uses a standardised checklist to record the frequency with which they are observed within a specific time frame
57
Structured Observation S+W
Easy to gather relevant data because you know what you are looking for
Interesting behaviours could go unrecorded because they weren't pre-defined as important
58
Unstructured Observation
The observer recalls all relevant behaviours but has no system
59
Unstructured Observation S+W
Interesting behaviours don't go unnoticed
Difficult to gather relevant data because you don't know what you are looking for
60
What is inter-rater reliability?
The test should give consistent results regardless of who administers it
This can be assessed by correlating the scores each researcher provides and compare. There should be an 80% agreement
61
How can inter-rater reliability be improved?
Offer a chance to discuss difficult issues or problems and monitor the quality of the data collection over time
62
Structured Interview
When the questions are decided in advance
63
Structured Interview S+W
Can be easily repeated (standardised questions)
Requires less skill than unstructured
Can be interviewer bias
Data collection will be restricted
64
Unstructured interview
Interviewees answers to questions guide subsequent questions
65
Unstructured Interview S+W
Detailed and in depth information obtained
Insight into feeling and thoughts
Affected by interviewer bias
Hard to analyse answers
66
Semi-Structured Interview
Combination of structured and unstructured
67
Qualitative data
Written form - words, texts, ideas
68
Quantative Data
Numbers and quantities
69
Reliability
Overall consistency of a measure
70
Internal Reliability
The extent to which a test is consistent within itself
71
Split-Half Method
## Footnote
Methods ensuring reliability
Compare an individual's performance on two halves of a test
72
Test-retest method
## Footnote
Methods ensuring reliability
A person repeats a test a month or so after doing the test the first time
73
Concurrent Validity
Results from a new test can be compared to a previously well-established test
74
Predictive Validity
If diagnosis leads to successful treatment then the diagnosis is seen as valid
75
Temporal Validity
Assesses to what degree research findings remain over time
76
Content Validity
Involves asking experts in the field to check the content of the study
77
Ecological Validity
Generalisable to real life settings- generalising findings from one setting to other settings
78
Population Validity
Whether you can reasonably generalise the findings from your sample to a larger group of people
79
Bar Chart and why its different to a histogram
Used to present discrete data that are placed into categories
Columns do not touch and have equal width and spacing
80
Histogram
Used to represent data on a continuous scale
81
What is correlation analysis?
When two or more variables are measured in order to see if there is a relationship
(positive, negative or no correlation)
82
Correlation coefficient
Number between 1 and -1 telling us how strong the correlation is
83
Types of Correlation
Positive - both variables increase
Negative - One increases the other decreases
No correlation- no relationship
84
Positive and Negative Skew
Positive -more scores on the lower end of the data set
Negative - more scores on the higher end of the data set
85
What is an experimental group?
The participants are the experiment who the researcher is testing
86
What is a control group?
The other condition where participants are taking part in the experiment, but no manipulation is used
87
What are demand characteristics?
Participants may have determined the aims of the study
88
How can demand characteristics be controlled?
Counterbalancing / randomisation
89
Name 2 self report methods
Questionnaires and Interviews
90
Interview
Used to gather qualitative data
91
Advantages and disadvantages of Interviews
Can get rich and detailed data
Time consuming and impractical
92
What are investigator effects?
Anything the researcher does which can effect how the participant behaves
93
What is researcher bias and how can it be avoided?
Researchers expectations can influence how they design their study.
Research assistant conducts the research using standardised procedures
94
What is content analysis?
Research analysing secondary data and data you've collected
95
Content analysis S+W
Inexpensive
Ethics - participants not directly involved
Subjectivity
Data analysis is time consuming
96
What is thematic analysis?
Making summaries of data and identifying key themes and categories
97
Mean
## Footnote
How its calculated and S+W
Adding up all the numbers and divide by the number of data items
Represents all the data
Effected by extreme values
98
Median
## Footnote
How its calculated and S+W
Middle value in an ordered list
Not affected by extreme values
Exact values not represented
99
Mode
## Footnote
How its calculated and S+W
Most common data item
Not affected by extreme values
Sometimes there are too many modes
100
Range
## Footnote
How its calculated and S+W
Difference between top and bottom values
Easy to calculate
Affected by extreme values
101
Standard Deviation
## Footnote
How its calculated and S+W
Measure of the average distance between each data item above and below the mean
Precise measure of dispersion
Affected by extreme values
102
Quantitative Data
Numbers
103
Primary Data
Data collected first hand by the researcher
104
Secondary Data
Data collected from another source
105
Pilot Study
A small scale investigation that takes place before the real investigation is conducted
106
Questionnaires
Set of questions used to assess a person's thoughts and experiences
107
Questionnaires S+W
Produces quantitative data
Easily repeatable
Answers maybe chosen that don't represent real thoughts
Poor/vague questions lead to incorrect results
108
Case study Definition + S+W
Intense description of a single individual case
Rich data, unique cases studied in detail
Can't be generalised
109
What is a sample?
The people the researcher actively use in the research
110
5 sampling techniques
Opportunity
Volunteer
Random
Stratified
Systematic
111
Random Sampling
Each person has an equal chance of being selected. Chosen by a computer random generator
112
Random Sampling S+W
Fair
More likely to be representative
Can be biased if the sample is too small
113
Volunteer
## Footnote
Sampling method
People who are interested apply to be in the research
114
Volunteer S+W
## Footnote
Sampling method
Convenient and ethical
Sample is biased because the participants are likely to be more motivated (volunteer bias)
115
Opportunity
## Footnote
Sampling Method
The participants available at the time to take part in the research
116
Opportunity S+W
## Footnote
Sampling Method
Easy and quick method because you just use the first participants you find
Biased as the sample is drawn from a small part of the target population
117
Stratified
## Footnote
Sampling method
Selective people from every portion of your populations - in the same proportions
118
Stratified S+W
## Footnote
Sampling method
More representative
Time consuming as all participants need to be assessed and categorised
119
Systematic Sampling
Selecting every nth name from a list
120
Systematic Sampling S+W
Avoids bias as there is no control over who is being selected
Not necessarily representative if the pattern used for the sample coincides with a pattern in the population
121
Nominal
## Footnote
Levels of measurement
Data represented in the form of categories
122
Ordinal
## Footnote
Levels of measurement
Data which is ordered in some way
123
Interval / Ratio
## Footnote
Levels of measurement
Numerical scales that include units of equal precisely defined size
124
What part of the research report should include the psychologists hypothesis
The introduction
125
What are the 5 ethical guidelines?
Informed consent
Deception
Right to withdraw
Confidentiality
Protection from harm
126
External Validity
The extent the results of the study can be generalised to others
127
Internal Validity
The study measures or examines what it claimed to measure or examine
128
4 Aims of Peer review
* Assess the appropriateness of the research to the research topic/aim
* Check the validity of the findings
* Judge the significance of the research
* Check that the research is original and has not been plagiarised
129
Role of Peer Review
It helps to determine if the research can be deemed scientifically acceptable
Peer review is an independent assessment carried out before the research is published by other experts in the field
It is completed independently and usually anonymously
130
3 Types of Peer review
* Single Blind (researcher's name is not revealed to the reviewers)
* Double Blind (researcher and the reviewers are anonymous to each other)
* Open Review (researcher and reviewer known to each other)
131
Evaluation of Peer review
* Reviewers are especially critical of research that contradicts their own
* Reviewers tend to be established scientists and are more likely to publish research that ‘fits’ with current opinions
* This could slow down the rate of change
132
Implications of research for the economy
Psychological research involves real people, investigating real behaviours which have real consequences
133
Implications of research for the economy evaluation
Absences at work cost the economy an estimated £15 billion per year
-a third caused by depression, anxiety and stress (the telegraph 2014)
-CBT/SSRIs and anti anxiety drugs have allowed people with mild mental health disorders to return to work and access medical treatment
134
Features of a psychological report
Title
Abstract
Introduction
Method
Findings
Discussion
Appendix
135
Title
Should say what the study is about and include the independent and dependent variables
136
Abstract
Short summary that includes all the major elements: the aims and hypotheses, method/procedure, results, and conclusions
137
Introduction
* Literature review of the general area of investigation
* Look at the relevant theories, concepts, and studies
* Should follow a logical progression, beginning broadly then becoming more specific until aims & hypotheses are presented
138
Method
Footnote ##
DS APE
Should include sufficient detail so that other researchers are able to replicate the study
* Design - (eg independent groups, naturalistic observation etc) and reasons/justification given for choice
* Sample - amount of p's, biographical/demographical info (avoiding compromising anonymity), sampling method, target pop.
* Apparatus/materials - detail of any assessment instruments used & other relevant materials
* Procedure - list of everything that happened, including briefing, standardised instructions, and debrief
* Ethics - how these were addressed within the study
139
Results
Summary of key findings from investigation
* Descriptive statistics eg tables, graphs, charts, measures of central tendency, and measures of dispersion
* Inferential statistics eg reference to choice of statistical test, calculated & critical values, level of significance, final outcome (which hypothesis rejected)
* Any raw data & calculations appear in appendix rather than main body of report
140
Discussion
Summary of findings in verbal form
* Relationship of results to previous research (mentioned in intro)
* Limitations of study & suggestions of how these might be addressed in a future study
* Wider real-world implications of research
141
When to use the Sign test
The assumptions of the sign test:
• we are looking for a difference not an association
• we need to use a repeated measures design
• we need data that is organised into categories- nominal data
142
Using the Sign Test
* Calculate difference between the two sets of data (just state +/-/0)
* Add up positives and negatives and ignore zeros (eg -=6 and +=2)
* The less frequent sign is your S value (2 in this case)
* The N is number of participants minus the zeros (eg 10 participant but 2 had no significance and 2 were positive so N=6)
* Add S+N (2+6)
* Compare S with the critical value using N=8 (level of significance assumed to be 0.05)
* Critical value needs to be greater than S for it to be considered significant
143
Levels of significance and probability
• all statistical tests employ a significance level
• you can reject the null hypothesis and claim you have found a significant difference/correlation
• However: there is a 5% probability that the observed effect occurred by chance
144
The Rule of R
| How to tell if calculated value is significant
Statistical tests (eg Spearman’s Rho) with an R in the name are those whose calculated value must be equal to or more than the critical value to be significant
145
(Significance and probability) How to use the table
-one-tailed or two-tailed: probability levels double when two-tailed tests are being used for a more conservative prediction
-the number of participants: n value in the table/ however sometimes use the degrees of freedom (df)
-the level of significance: p value
146
Type I errors
When a true null hypothesis is rejected, meaning a conclusion is drawn that there is a significant effect when there isn't one
147
Type II errors
When a false null hypothesis is not rejected, meaning a significant effect is missed when it actually exists
148
Difference between Type l and Type ll errors
Type l is a false positive
Type ll is a false negative
149
When to use Mann Whitney test
* a test of difference
* testing between independent groups
* using ordinal data - scores
150
When to use Wilcoxon
a test of difference for related data that is ordinal
experimental design can be repeated measures or matched pairs
calculated value is the sum of the numbers of the less frequent sign (+ or -)
151
Chi Squared
-used when
• test of difference or association/correlation
• the data is nominal and recorded as a frequency
• independent groups design- unrelated data
uses contingency table
looks for observed frequency
152
Paradigm shifts
A paradigm shift, as identified by Kuhn (1962), is an important change in the basic concepts and experimental practices of a scientific discipline. It is a change from one way of thinking to another
153
Paradigms
The basic assumptions, ways of thinking, and methods of study that are commonly accepted by members of a discipline or group.
154
What is a theory?
A set of general laws that have the ability to explain
particular events or behaviours
155
How do Theory constructs occur?
Through gathering evidence via direct observations (the empirical method)
156
Falsifiability
* Popper (1934) ‘genuine scientific theories should hold themselves up
for hypothesis testing and the possibility of being proven false’
* Even ‘proven’ research is not true, it has just not yet been proven false!
157
Replicability
- Trusted findings should be repeatable across a number of contexts and circumstances
- Validity and reliability
158
Objectivity and the empirical method
• ‘critical distance’
• Controlled laboratory studies
• Experience- knowledge is determined only by experience and sensory
perception (Locke)
159
The case for psychology being a science
• Key findings in psychology are counter-intuitive and not predictable
• Psychology gained credibility by adopting scientific methods of
enquiry
• Practical application and challenged/ modified human behaviour
160
The case against psychology being a science
* Methods can be subjective, non-standardised and unscientific
* Based on inference rather than objective measurement
161
Spearman’s Rho
• test of correlation
• used for two sets of values at an ordinal or one interval one ordinal
162
Pearson’s R
• Interval data and a test of correlation
• the closer r is to -1 or +1 the stronger the relationship
163
Related T-test
• repeated measures design or matched pairs
• test of difference with interval or ratio data
• e.g. weight in kg
N-1
164
Unrelated T-test
• independent groups
• interval data is needed
• test of difference
Degree of Freedom= N1+N2-2
165
Statistical Tests table
166
3 Types of Data (NOI)
Nominal - categories (who walks to school, drives, cycles etc)
Ordinal - ordered in some way (scale from 1-10)
Interval - units of evenly spaced measurements (height time temp)
167
3 Statistical Tests that use Repeated Measures/ matched pairs design
Sign, Wilcoxon, Related T tests
168
3 Statistical tests that use independent groups
Chi Squared, Mann Whitney, Unrelated T tests
169
Statistical Tests that use association
Chi Squared
170
Statistical Tests that use correlation
Spearmans Rho, Pearson R
171
Statistical Tests that use Nominal data
Chi Squared and Sign
172
Statistical Tests that use Ordinal data
Mann Whitney, Wilcoxon and Spearmans Rho
173
Statistical Tests that use Interval
Unrelated, related and pearson r
