Research Methods 1 &2 Flashcards
1
Q
Experimental method
A
Involves the manipulation of an independent variable to measure the effect on the dependent variable
Can be Laboratory, field, natural or quasi
2
Q
Aim
A
A general statement of what the researcher intends to investigate
Purpose of the study
3
Q
Hypothesis
A
Clear, precise, testable statement that states the relationship between the variables to be investigated
4
Q
Directional Hypothesis
A
States of the direction of the difference or relationship
5
Q
Non-directional Hypothesis
A
Does not state the direction of the difference or relationship
6
Q
Variables
A
Any thing that can vary or change within an investigation
Variables are generally used in experiments to determine if changes in one thing results in changes in another
7
Q
Independent variable
A
aspect of experiment that is manipulated by the resercher
or changes naturally
8
Q
Dependent variable
A
The variable that is measured by the researcher
9
Q
Operationalisation
A
clearly defining variable in terms of how that can be measured
10
Q
Extraneous Variable
A
Any variable (other than IV) that may affect the dependent variable if it isn’t controlled
Nuisances
11
Q
Confounding variables
A
A kind of EV that varies systematically with the IV
Can’t tell if change in DV is to do with IV or confounding variable
12
Q
Demand characteristics
A
Any cue from researcher or situation that may be interpreted by ppts as revealing the purpose of the investigation
This may lead to the participants changing their behaviour
13
Q
Investigator effects
A
Any effect of the investigators’s behaviour (conscious or unconscious) on research outcome
eg. design of the study, interaction with ppts
14
Q
Randomisation
A
Use of chance in order to control the effects of bias when designing materials and deciding the order of conditions
15
Q
Standardisation
A
Using exactly the same formalised procedures ad instructions for all participants
16
Q
Experiment design - Independent groups
A
Participants allocated to different groups, each group is an experimental condition
Group 1 does condition A
Group 2 does condition B
17
Q
Evaluate Independent groups design
A
People in the groups are different so participant variables may have an effect on DV
Random allocation can help with this
More expensive as you have pay 2 groups of people
Order effects are not a problem
Ppts unlikely to guess aim
18
Q
Experiment design - Repeated Measures
A
All participants take part in all conditions of the experiment
Group 1 does condition A and B
19
Q
Evaluation of Repeated Measures
A
Order tasks might be significant
Order effects may arise as ppts may get bored or tired
= deteriation in performance or practice = confounding variable
Ppts might work out the aim
Ppt variables controlled
Fewer ppts needed = cheaper
20
Q
Experimental design - Matched Pairs
A
Pairs of ppts matched on some variables that affect DV
One of the pair does condition A the other does condition B
21
Q
Evaluation of Matched Pairs
A
Ppts only take part in one condition so order effects and demand characteristics are less of a problem
Reduced participant variables but still an issue
Time consuming and expensive
22
Q
Random Allocation
A
Attempt to control for participant variables in independent groups design which ensures that each participant has the same chance of being in any condition
23
Q
Counterbalancing
A
An attempt to control for the order effects in repeated measure design
Half the ppts experience the conditions in one order and the rest experience it in the other order
24
Q
Lab experiments
Strengths and Weaknesses
A
Experiment that takes place in a controlled environment within which the researcher manipulates the IV and records effect
Strengths- high control over EV, high internal validity, replication easy so findings are valid
Weaknesses- lack generalisability, not realistic, low external validity, demand characteristics are likely, low mundane realism
25
Field Experiments
Strengths and Weaknesses
An experiment that takes place in a natural setting within which the researcher manipulates the IV
Strengths- high mundane realism, high external validity,
Weaknesses- less control over EV, harder to establish the cause and effect, ethical issues if ppts aren't aware they aren't being watched
26
Natural Experiment
Experiment where the change in the IV is not brought about by the researcher, would have happened anyway,, Effect on DV is recorded
Strengths- allow us to do research that otherwise wouldn't be possible for ethical or practical reasons, high external validity
Weaknesses- these events are very rare, can't randomnly allocate the ppts, less sure if IV affects the DV,
27
Quasi Experiment
Strengths and Weaknesses
Not an experiment as it doesn't have a determined IV, variables such as being young or old simply exist
Strengths- controlled, high internal validity, easily replicated
Weaknesses- there are likely to be confounding variables
28
Population
Group of people who are the focus of the the researcher's interest, from which a smaller sample is drawn
29
Sample
A group of people who take part in a research investigation drawn from a target population and presumed to be representative of that population
30
Bias
When certain groups may be over or under-represented within the sample
This limits the extent to which generalisations can be made
31
Generalisation
The extent to which findings and conclusions from a particular investigation can be broadly applied to the population
This is possible if the sample of participants is reprensentative of the population
32
Random sample
all members of the target population have an equal chance of being selected
Create a list of all members of the target population and assign them a number
Then use a rng or pick numbers out of a hat to select their sample
33
Random sample Evaluation
No researcher bias
Difficult and time consuming
May not be representative
Ppts may refuse to take part
34
Systematic Sample
Every nth member of the target population
Sampling frame has to be produced and interval determined
35
Systematic sampling Evaluation
No researcher bias
Can be fairly representative
Time consuming and difficult
36
Stratified sample
Composition of sample represents proportions of people in certain sub groups within target population
Identities the stratas and take a proportion from each
37
Oppurtunity Sample
Selecting anyone willing and available to take part and around at the time
asking people as they go in to a shop
38
Stratified sample Evaluation
Avoids researcher bias
Once ppts are selected they are randomly allocated
Produces representative sample
But can't reflect all the ways that people are different so it isn't possible
39
Opportunity Sample Evaluation
Convenient and quick and cheap
However it is very unrepresentative, so can't be generalised
Also the research chooses the ppts so lots of researcher bias
40
Volunteer Sample
Ppts select themselves to be part of the sample
Using adverts and or notice boards
41
Volunteer Sample Evaluation
Easy and quick
Requires minimal input from researcher
Volunteer bias is a problem - everyone volunteering has a certain profile
42
Ethical Issues
these arise when there is a conflict between the rights of the participants and the goals of the research
43
Informed consent
Making sure ppts are aware of the aims of the research, the procedure, their right to withdraw and what their data will be used for
researchers often feel asking for informed consent may make the study meaningless as their behaviour won't be natural
44
Ways to deal with Informed Consent
Ppts should be issued with a consent letter o form detailing all relevant information
For ppts under the age of 16 parental consent is required
45
Deception
Deliberately misleading or withholding information from ppts
If ppts have not received full information can not give informed consent
It can be justified
46
Ways of dealing with ethical issues
Ppts should be given a debrief at the end of the study where they are made aware of true aims and anything else they weren't told
They must also be told what their data is going to be used for and have the right to withhold it
Should be assured they did nothing wrong or abnormal
Offer counselling
47
Protection from Harm
Ppts shouldn't be in any more risk than they would normally
Psychologically or physically
Including embarrassment, stress, feeling inadequate
Remind ppt that they have the right to withdraw
48
Dealing with protection from Harm
Ppts should be given a debrief at the end of the study where they are made aware of true aims and anything else they weren't told
They must also be told what their data is going to be used for and have the right to withhold it
Should be assured they did nothing wrong or abnormal
Offer counselling
49
Privacy and Confidentiality
Ppts control their information
Under the Data Protection Act, any personal data must be protected
Extends to the area where the study took place, locations should not be named
50
Dealing with Confidentiality
Maintain Anonymity
Use things such as initials in case studies
Regularly remind ppt that their data will be protected
51
BPS code of ehtics
Quasi-legal document
Instructs psychologists in the UK about what behaviour is acceptable when dealing with ppts
Built around respect, competence, responsibility and integrity
Implemented by ethics committee
If you break them, you won't go to prison but you might lose your job
52
Pilot studies
Small scale version of an investigation that takes place before the real investigation is conducted
Aim is to check that procedures, materials, measuring scales work to allow the researcher to make changes or modifications if necessary
53
Single-blind procedure
Ppts are not told the aim and some other details at the beginning of the study
Attempt to control for confounding effects of demanding characteristics
54
Double Blind Procedures
Neither ppt or researcher conducting experiment is aware of aims
Important in drug trials so neither patient or person administering drug knows wich drugs are real and which are placebo
55
Control groups and conditions
In a drug trial
Group that receives real drug is experimental group/condition
Group that receives placebo is control group/condition
56
Naturalistic Observation
Watching and recording behaviour in the setting within which it would normally occur
Useful for studying interactions
57
Evaluation of Naturalistic Observations
High external validity
Can usually be generalised to everyday life
Uncontrolled extraneous variables
58
Controlled Observations
Watching and recording behaviour within a structured environment
Some variables are managed
59
Controlled Observation Evaluation
Can't be applied to real life
Extraneous variables are less of an issue
Easier to replicate
60
Covert observation
Ppts behaviour is watched and recorded without their knowledge or consent
Behaviour must be public to make it ethical
61
Covert Observation Evaluation
Removes participant reactivity
Behaviour is natural
Increases the validity of the data
Ethical issues - people don't want their behaviours recorded
62
Overt observations
Ppts behaviour is watched and recorded with their knowledge and consent
63
Overt Observation Evaluation
More ethically acceptable
Them knowing they are being watched may affect their behaviour
64
Participant Observation
The researcher becomes a member of the group whose behaviour they are watching and recording
65
Participant Observation Evaluation
Gives them increased insight
Increase validity
Reseracher may lose objectivity
Might affect ppts and therefore findings
66
Non-participant Observation
Researcher remains outside of the group whose behaviour they are watching
67
Non-participant Observation Evaluation
Allow the researcher to maintain objective
Less insight
68
Behavioural Categories
When a target behaviour is broken up into components that are observable and measurable
69
Evaluation of behavioural categories
makes data collection mroe structured and objective
Categories must be clear and unambiguous
Behaviours must be observable, measurable and self-evident
This can be difficult
All possible forms of target behaviour are included - no dust bin category
categories should be exclusive, no overlap
70
Event Sampling
Target behaviour or event is first established then the researcher records this event every time it occurs
71
Event Sampling Evaluation
Useful if it happens infrequently
Not useful if event is very complex
72
Time sampling
A target individual or group is first established then the researcher records heir behaviour in a fixed time frame eg. every 60 seconds
73
Time sampling Evaluation
Reduces the number of observations needed to be made
It might be unrepresentative
74
Questionnaire
Set of written questions used to assess a person's thoughts and/or experiences
75
Open Question
Respondents are free to answer in any way they wish, no fixed range
Produces Qualitive data
Difficult to analyse
76
Closed Question
fixed responses
yes/no or number answers
Produces Quantitive data which is easier to analyse
Lacks the detail
77
Strengths of Questionnaires
Cost-effective
Useful for large groups
Researcher doesn't need to be there
Easy to analyse
78
Limitations of Questionnaires
Responses aren't always reliable
Social desirability bias - people want to present themselves in a positive light
Response bias -always answering yes
79
Interviews
Live encounter where the interviewer asks a set of questions to assess an interviewees thoughts and experiences
80
Structured interviews
Pre-determined set of questions asked in a fixed order
Face to face questionnaire
81
Unstructured interviews
No set questions
More like a conversation
Interviewee is encouraged to expand and elaborate
82
Semi-structured interviews
Most common
Lies somewhere between structured and unstructured
List of questions but interviewer can ask follow up questions if desired
83
Structured interviews evaluation
Easy to replicate
Limits data collected, less detail on unexpected information
83
Unstructured interviews evaluation
Gain more insight and detail
Risk of Interviewer bias
Difficult to analyse
Social desirability bias
84
Correlation
Mathematical technique in which the researcher investigates an association between 2 variables
Shown with scatter graph
85
Co-variables
The variables investigated within a correlation
Not independent or dependent variables because they are looking at the association rather than cause-effect
86
Positive Correlation
As one co-variable increases so does the other
(diagonal line up)
(y=x)
87
Negative Correlation
As one co-variable increases the other decreases
(diagonal line down)
(y=-x +c)
88
Zero correlation
No relationship between the co-variables
No line of best fit
89
Correlation Strengths
Precise measurement of how how 2 variables are related
Starting point for experiments
Quick and economical
Can use secondary data
90
Correlation Limitations
Often lack control
We can see how they are related but not why
There could be an intervening variable
Relationships can be presented as causal
91
Qualitative data
Data that expressed in words and non-numerical
(it can be converted for analyses)
Detailed
From unstructured interveiws
92
Quantitative data
Data that can be counted, usually given as numbers
93
Primary Data
Information that has been obtained first-hand by a esearcher for the purpose of a research project
Gathered from ppts
94
Secondary Data
Information that has already been collected by someone else
Pre-dates current research project
Eg. other psychologists work or government statistics
95
Meta analysis
Combining the findings from a number of studies on a particular topic.
Aim to produce an overall statistical conclusion based on a range of studies
Not to be confused with a review where many studies are compared and discussed.
96
Qualitive data Evaluation
More detail
Greater external validity
Hard to analyse
Conclusions therefore rely on subjective interpretations so may be subject to researcher bias
97
Quantitative data Evaluation
Easy to analyse
Comparisons can be drawn easily
Objective data
Narrow detail
Less realistic
98
Primary data Evaluation
Authentic data, exactly the right data for your study can be obtained
Requires time and effort including planning and prep
99
Secondary data Evaluation
Cheap and easy
Considerable variation in quality of secondary data
Also it might be applicable but it might not
might be outdated
100
Meta-analysis Evaluation
Results can be generalised across larger populations
Can be prone to publication bias - researcher may leave some studies out because they may have negative results
101
Descriptive statistics
Use of graphs, tables and summary statistics to identify trends and analyse sets of data
102
Measure of central tendency
The general term for any measure of the average value in a set of data
103
Mean
The arithmetic average calculated by adding up all the values in a set of data and dividing by the number of values there are
104
Median
The central value in a set of data when values are arranged from lowest to highest
105
Mode
The most frequently occurring value in a set of data
106
Measures of dispersion
The general term for any measure of the spread or variation in a set of scores
107
Range
Simple calculation of the dispersion in a set of scores which is worked out by subtracting the lowest score from the highest score and adding one
108
Standard deviation
Sophisticated measure of dispersion in a set of scores
Tells us how much scores deviate from the mean by calculating the the difference between the mean and each score
All the differences are added up and divided by the number of scores
109
Scattergram
A type of graph that represents the strength and direction of the relationship between co-variables in a correlational analysis
110
Bar Chart
A type of graph in which the frequency of each variable is represented by the height of the bars
111
Histogram
A type of graph which shows frequency but unlike a bar chart, the area of the bars represents frequency.
The x-axis must start at a true zero and the scale is continuous
112
Normal distribution
A symmetrical spread of frequency data that forms a bell shaped pattern
The mean, median and mode are all located at the highest peak
113
Skewed distribution
A spread of frequency data that is not symmetrical, where the data clusters to one end
114
Positive skew
Long tail is on the positive (right) side of the peak
Most of the distribution is concentrated on the left
115
Negative Skew
Long tail is on the negative (left side of the peak so most of the distribution is concentrated on the right
116
Statistical Testing
Provides a way of determining whether hypotheses should be accepted or rejected
We can find out whether differences or relationship between variables are statistically significant or occurred by chance
117
Sign test
Used to analyse the difference in scores between related items
Data is nominal
Significance level - 5%
Number of ppts - N
Number of less frequent sign - S
S must be equal or less the critical value at 5% for it to be significant
118
Peer Review
The assessment of scientific work by others who are specialists in the same field to ensure that any research intended for publication is of high quality
119
Main aims of Peer Review
To allocate research funding
To validate the quality and relevance of research
To suggest amendments or improvements
120
Peer Review Evaluation
It should be anonymous but when there are few psychologists in an area it isn't and reviewers may be influenced by this
People only want to publish headline grabbing, positive findings giving a false impression of current state of psychology
Supresses opposition to mainstream research. Researchers tend to be critical of research that contradicts there own
So peer review can slow down rate of change
121
Economy
The state of a country or region in terms of the production and consumption of goods and services
122
Implications of attachment research on economy
Role of the father
- studies suggest that fathers have different but just as crucial role
-promotes more flexible working hours
- allows women to work more
123
Implications of research into treatments for mental illness
Absence from work costs the economy £15 billion a year
Treating depression will allow people to get manage their condition and return to work
124
Case Studies
An in-depth investigation, description and analysis of a single individual, group, institution or event
125
Case Studies Strengths
Rich an detailed insights on rare forms of behaviour
Increase understanding of 'normal' behaviour
can generate hypotheses for future study
126
Case Studies Limitations
Can't generalise
Subjective selection and interpretation of data
Low validity
127
Content Analysis
A research technique that enables the indirect study of behaviour by examining communications that people produce
128
Coding
The stage of content analysis in which the communication to be studied is analysed by identifying each instance of the chosen categories
Quantitative data
129
Thematic Analysis
An inductive and qualitative approach to analysis that involves identifying implicit or explicit ideas within the data.
Themes will often emerge once the data has ben coded
Qualitive data
130
Content Analysis Strengths
Circumnavigates ethical issues
Most of the material they require is publicly available
High external validity
Flexible
131
Content Analysis Limitations
Indirect
So researcher may impose opinions and motivations on the speaker
Can lack objectivity
132
Reliability
Refers to how consistent the findings from an investigation or measuring device are
A measuring device is said to be relaible if it produces consistent results every time it is used
0.8
133
Test-retest
Method of assessing the reliability of a questionnaire or psychological test by assessing the same person on two separate occasions
Shows to what extent the test produces the same answers
134
Inter-observer reliability
The extent to which 2 observers involved in observing of a behaviour.
This is measured by correlating the observations of two or more observers.
Total number of agreements
--------------------------------------------- > 0.8
Total number of observations
135
Improving reliability - Questionnaires
Use questionnaires to do test retest
a questionnaire with low test-retest may require some questions to be removed or rewritten
Fixed choice questions are less ambiguous so improve test-retest score
136
Improving reliability - Interviews
Ensure to use the same interviewer
Train interviewers to avoid leading questions
Unstructured interviews are more free-flowing are less reliable
137
Improving reliability - experiments
Lab experiments can be more reliable as the researcher can exert more control over variables.
137
Improving reliability - experiments
Lab experiments can be more reliable as the researcher can exert more control over variables.
Allows for more precise replication of particular method.
138
Improving Reliability - Observations
Can be improved by operationalising behavioural categories
If categories overlap it may give inconsistent results
139
Validity
The extent to which an observed effect is genuine.
Does it measure what is was supposed to measure, and can it be generalised beyond the research setting within which it was found
140
Face Validity
A basic form of validity in which a measure is scrutinised to determine whether it appears to measure what it's supposed to measure.
141
Concurrent Validity
The extent to which a psychological measure relates to an existing similar measure
142
Ecological Validity
The extent to which findings from a research study can be generalised to other settings and situations. A form of external validity.
143
Temporal Validity
The extent to which findings from a research study can be generalised to other settings and situations.
Form of external validity
144
Internal Validity
Refers to whether observed effects are due to the manipulation of the IV and not some other factor.
145
Improving Validity - Experimental research
Use a control group.
Use standardised procedures to reduce the impact of investigator effects and participant reactivity.
146
Improving Validity - Questionnaires
Lie scale to assess the consistency of ppts response and control effects of social desirability bias
147
Improving Validity - Observations
Have high ecological validity as researcher doesn't interfere.
Behavioural categories can effect validity though
148
Improving Validity
