1
Q
Operationalising Variables
A
Any method in which a person is asked to state or explain their own feelings, opinions, behaviours and experiences related to a given topic.
2
Q
Questionairre
A
A set of written questions (sometimes called items) used to access a persons’ thoughts/experiences
3
Q
Strengths of questionnaires
A
+ Cost effective
+ Can gather large amounts of data quickly
+ Can be completed without the researcher being present
4
Q
Single-blind review
A
- usual form of peer review
- involves the names of reviewers not being revealed to the researcher
5
Q
Weaknesses of questionnaires
A
- Can produce response bias
- P.ps may misunderstand the question or read it incorrectly
- Demand Characteristics / Social Desirability may occur
6
Q
Open review
A
the reviewers and the researcher being known to each other
7
Q
Double-blind review
A
both the reviewers and the researcher are anonymous
8
Q
Questionnaire construction
A
Aims, length, previous questionnaires, question formation, pilot study, measurement scale
9
Q
Advantages & Disadvantages of an Open Question
A
+ Get more information
+ Produces qualitative data - depth and detail
- People can miss them out as they can’t be bothered to answer them
- Harder to analyse
10
Q
Closed Question
A
Questions with a fixed answer/ the choice of response is determined by the question setter.
11
Q
Advantages & Disadvantages of a Closed Question
A
+ People have to same perception of the Q&A
+ Quick and easy to answer
+ Quantitative data is easier to analyse
- Not detailed or in depth answers
- Don’t find out the meaning behind the answer
12
Q
Interview
A
A live encounter (face to face or on the phone) where one person asks a set of questions to assess an interviewees thoughts/experiences. They can be structured, semi structured or unstructured.
13
Q
Structured Interview
A
Made up of pre-determined questions and are asked in a fixed order. Basically like a questionnaire but conducted face to face.
14
Q
Unstructured Interview
A
Works like a conversation. There are no set questions. There is a general aim that a certain topic will be discussed and interaction tends to be free flowing.
15
Q
Semi-structured Interview
A
There is a list of questions that have been worked out in advance but interviewers are also free to ask follow up questions when they feel it is appropriate.
16
Q
Strengths & Weaknesses of Structured Interview
A
+ Straight forward to replicate
+ Reduces differences between interviews
+ Easier to analyse
+ Get answers you’re looking for
- Get less information as P.ps can’t deviate from the point
- Don’t find out people’s worldwide views
17
Q
Strengths & Weaknesses of Unstructured Interview
A
+ Can get more detailed answers as people can elaborate
+ More flexible as you can gain insight
- Not easy to replicate
- Not easy to analyse as you get irrelevant information
- Experimenter effects can occur
18
Q
Design of interviews
A
Gender and age, ethnicity, personal characteristics and adopted role
19
Q
Leading Questions
A
Encourages P.ps to give a particular answer e.g don’t you think…?
20
Q
Ambiguity
A
Questions which can be interpreted in various ways. They can mean different things to different people.
21
Q
Loaded Questions
A
They are questions which contain emotive language which is likely to produce an emotional reaction in the respondent.
22
Q
Double-barreled Questions
A
They contain two options within a single question.
23
Q
Aim
A
A general statement that the researcher intends to investigate.
24
Q
Hypothesis
A
A detailed statement which is clear, precise and testable that states the relationship between variables being tested.
25
Directional Hypothesis
The researcher makes it clear what difference is anticipated between the 2 conditions or groups.
(One tailed).
26
Non-directional Hypothesis
Simply states that there is a difference but not what the difference will be.
27
Null Hypothesis
There will be no relationship between the 2 variables.
28
Meta-analysis
A particular form of research method that uses secondary data. Data from a large number of studies which have involved the same research question and method are combined.
29
Qualitative Data
Data that describes meaning and experiences which is expresses in words e.g. case studies, interviews and observations.
30
Primary Data
Information that has been obtained first hand by the researcher. It is also known as field research.
31
Secondary Data
Information that has already been collected by previous researchers. It is also known as 'desk research' and can be found in journal articles, books or websites.
32
Ethical issues
the rules governing the conduct of researchers in investigations
33
Informed Consent
Participants should be told what they are letting themselves in for. Only then they are in a position to give informed consent. If under 16 consent must be obtained from their parents.
34
Deception
Information is withheld from participants: they misled about the purpose of the study and what will happen during it.
35
Right to Withdraw
Participants should be told this at the start of the research. No attempt should be made to encourage them to remain.
36
Protection from harm
Participants should not be put through anything they wouldn't normally be expected to.
37
adequate briefing/ debriefing
all relevant details of a study should be explained to participants before and afterwards
38
Observational research
observations are only made in public places where people might expect to be observed by strangers
39
incentives to take part
participants should not be offered bribes or promised rewards for their participation
40
Variable
Any "thing" that can vary or change with in an investigation. They are generally in experiments to determine if changes in one result in changes to another.
41
Independent Variable - IV
An aspect of the experimental situation that is manipulated by the researcher or changes naturally so the effect on the DV can be measured.
42
Dependent Variable - DV
The variable that is measured by the researcher. Any result/change on the DV should be caused by the change in the IV.
43
Operationalising Variables
The process of devising a way of measuring a variable. It is a clear statement of what the variable is.
44
Lab Experiment
An experiment that takes place in a controlled environment where the researcher manipulates the IV and records the effect on the DV while maintaining strict control of extraneous variables.
45
The Criteria for a Lab Experiment
1) The IV is manipulated by the researcher to produce a change in the DV
2) All other variables that might influence the results i.e. extraneous variables are held constant or eliminated
3) Participants are randomly allocated to a condition.
46
Advantages of a Lab Experiment
+ Can establish cause and effect
+ Few if any extraneous variables
+Easy to replicate
+High internal validity
47
Disadvantages of a Lab Experiment
- Lacks ecological / external validity
- Demand characteristics can occur
- Behaviour in a lab is often different
- Experimenter effects can occur
48
Reliability
the extent to which a test or measurement produces consistent results
49
Validity
the extent to which results accurately measure what they are supposed to measure
50
Internal validity
concerns whether results are due to manipulation of the IV and have not been affected by confounding variables
51
External validity
refers to the extent to which an experimental effect (results) can be generalized to other settings
52
Face validity
assessing validity and involves the extent to which items look like what a test claims to measure
53
Concurrent validity
assesses validity by correlating scores on a test with another test known to be valid
54
The scientific process
Popper- a means of acquiring knowledge based on observable, measurable evidence
55
Replicability
being able to repeat a study to check the validity of the results
56
Objectivity
observations made without bias
57
Falsification
that scientific statements are capable of being proven wrong
58
Inductive phase
observations yield information that is used to formulate theories as explanations
59
Deductive phase
Predictions made from theories, in the form of testable hypotheses, are tested and yield data that is analysed, leading to theory adjustment
60
Paradigm shifts
revolutionary changes in scientific assumptions
61
Predictive validity
predicting how well a test predicts future behaviour
62
Temporal validity
assesses to what degree research findings remain true over time
63
Field Experiment
An experiment that takes place in a natural setting where the researcher manipulates the IV and records the effect on the DV.
64
Advantages of a Field Experiment
+ More ecologically/externally valid
+ Fewer demand characteristics
+Replication can occur to some extent
+ Fewer experimenter effects
65
Disadvantages of a Field Experiment
- Chance of extraneous variables
- More time consuming
- Ethical issues (informed consent)
- Need a skilled researcher
66
Natural Experiment
An experiment where the change in the IV is not caused by the researcher as it would have happened if the researcher wasn't there. The researcher records the effect on the DV.
67
Advantages of a Natural Experiment
+ No demand characteristics
+ No researcher effects
+ Fewer ethical issues
+ Allows P.ps who wouldn't normally be tested to take part.
68
Disadvantages of a Natural Experiment
- Lack of control (extraneous variables)
- Short term behaviour may be displayed
- No random allocation can create confounding variables
- Harder to replicate
69
Quasi Experiment
The IV has not been determined by anyone the variables simply exist e.g. being old or young.
70
Extraneous Variables
Any variable apart from the IV which can effect the DV if not controlled. However they can be maintained or eliminated.
71
Confounding Variables
A variable apart from the IV which can effect the DV. However it can't be controlled.
72
Control Condition
The IV isn't changed and provides a baseline measure. the condition is in a repeated measures design that provides a baseline measure of behaviour.
73
Experimental Condition
Where you manipulate the IV. The condition is in a repeated measures design containing the IV as distinct from control.
74
Baseline Measure
Result established from control condition when no manipulation of IV occurs. Allows comparisons to be made.
75
Random Allocation
People are chosen randomly e.g. names from a hat meaning there's an equal chance of being selected.
76
Ecological Validity
How methods can be applied to real life settings.
77
External Validity
How valid results are outside of a research setting.
78
Demand Characteristics
Any cue from the researcher or research situation that can be interpreted by participants as revealing the purpose of the investigation leading them to changing their behaviour.
79
Experimenter Effects
Where the experimenter changes a persons views usually sub-consciously through body language.
80
Experimental Methods
The type of experiment you do.
81
Experimental Designs
How you carry the experiment out.
82
Independent Groups Design
Each participant either does the control condition OR the experimental condition.
83
Advantages of Independent Groups Design
+ Reduces demand characteristics
+ Quick to administer
+ Could be used for all tests
+ Prevents order effects
84
Disadvantages of Independent Groups Design
- Individual differences can occur
- Lots of P.ps are required
- More time consuming
85
Repeated Measures Design
Each participant does the control condition AND the experimental condition.
86
Advantages of Repeated Measures Design
+ Quick to administer
+ No individual differences
+Fewer P.ps are required
87
Disadvantages of Repeated Measures Design
- High possibility of demand characteristics
- Order effects can occur
- Can't be used for all tests
88
Matched Pairs Design
Participants are matched on key characteristics. One participant does control condition and the other does the experimental condition.
89
Advantages of Matched Pairs Design
+ Less possibility of demand characteristics
+ Prevents order effects
+ No individual differences
90
Disadvantages of Matched Pairs Design
- Time consuming
- Lots of P.ps are required
- Hard to match P.ps on all variables
- Can't be used for all tests
- Not very economical
91
Counterbalancing
An attempt to control order effects in a repeated measures design e.g. ABBA where when group does the experimental condition first where as the other does the control condition.
92
Order Effects
A confounding variable arising from the order which participants take place in the different conditions e.g. boredom.
93
Naturalistic Observation
Take place in a setting where behaviour would usually occur.
94
Advantages & Disadvantages of Naturalistic Observations
+ High external validity
+ Easy to apply in everyday life
- Hard to replicate
- Extraneous variables can occur
95
Controlled Observation
Some control over variables takes place to observe how people may interact/behave. They take place inside and outside of a lab.
96
Advantages & Disadvantages of Controlled Observations
+ Easy to replicate
+ Less Extraneous Variables
- Findings can't be applied to all real life settings
97
Participant Observation
The researcher is involved in/with the experiment. The researcher joins the group either overtly of covertly.
98
Advantages & Disadvantages Participant Observations
+ Experience the same situation which gives insight which increases validity
- Can get too attached to people and lose objectivity
99
Non-Participant Observation
The researcher is not involved in what is going on. The researcher is external to what is going on/the people being observed.
100
Advantages & Disadvantages of Non-Participant Observations
+ Allows researcher to maintain an objective psychological distance from P.ps
- Researcher has less insight
101
Covert Observation
Where the researchers status is not made clear to the group and the researcher doesn't get consent.
102
Advantages & Disadvantages of Covert Observations
+ No participant reactivity
+ Natural Behaviour - Increases validity
- Ethics - People might not want to be observed`
103
Overt Observation
The researcher is open about their intentions and seeks consent. People know they are being observed.
104
Advantages & Disadvantages of Overt Observations
+ More ethically acceptable (have consent)
- Can be influenced as they know they're being watched
105
Structured Observations
Key influence of the design of an observation is how the data is recorded.
Unstructured- Everything is written down; produces qualitative data
Structured - Only specifics are recorded; produces quantitative data
106
Behavioural Observations
To produce a structured record of what the researcher hears or sees. The target behaviour is broken into behavioural categories that are observable and measurable. All target behaviour is included.
107
Sampling Methods
Event Sampling - Counting the time a particular behaviour occurs in a group/individual.
Time Sampling - Recording behaviour with a pre established time frame.
108
Inter-Observer Reliability
Two or more researchers observe the same behaviour at the same time then compare and amend results to create correlations.
109
Correlational analysis advantages
- allows predictions to be made
- allows quantification of relationships
- no manipulation
110
Correlational analysis disadvantages
- quantification problem
- cause and effect
- extraneous relationships
- only works for linear relationships
111
Content Analysis
a method of quantifying qualitative data through the use of coding units
112
Strengths of content analysis
- ease of application
- complements other methods
- reliability
113
Weaknesses of content analysis
- descriptive
- flawed results
- lack of causality
114
Target Population
The entire group a researcher is interested in. The researchers wishes to draw conclusions from only the people in the group.
115
Bias - sampling
When certain groups are over or under represented with in the sample selected. It limits the extent to which generalisations can be made to the target population.
116
Generalisation
The extent to which findings and conclusions from a particular experiment can be broadly applied to the population. This is possible if the sample of people is representative of the population.
117
The test-retest method
measures external reliability, by giving the same test to the same participants on two occasions
118
External reliability
concerns the extent to which a test measures consistently over time
119
Internal reliability
concerns the extent to which something is consistent within itself
120
The split-half method
measures internal reliability by splitting the test into two and having the same participant do both halves
121
Peer Review
The assessment of work by others who are specialists in the same field to ensure that any research set for publication is high quality.
122
How is psychological research published?
Initially in journals which will then be translated into textbook information or be discussed at conferences,.
123
Aims of Peer Review
1) To allocate funding properly and appropriately. It stops researchers spending lots of money on investigations which may encounter problems. Also it helps to develop the areas of psychology that need to be developed,
2) To validate the quality of research. It establishes more accurate to inter-observer reliability. Additionally it makes sure that you are measuring what you set out to measure.
3) To suggest amendments and improvements. It allows researchers to get more accurate results as it eliminates potential problems.
124
Evaluation of Peer Review
+ Helps to establish validity and accuracy of research because more than one person will carry out the experiment therefore allowing the data to be correlated.
- The anonymity could lead to them being overcritical . Changing data which is right and doesn't need to be changed could give inaccurate results and may not be objective as they should be
- Publication Bias can occur where only positive results or attention grabbing results are published. By publishing data which doesn't support a hypothesis, it allows it to have more understanding and knowledge.
125
Case Study
A research method that involves a detailed study of a signal individual, institution or event.
126
Sampling Techniques
The method used to select people from the population.
127
Opportunity Sampling
A sample of participants produced by selecting people who are most easily available at the time of the study.
128
Opportunity sampling advantages
- ease of formation
| - natural experiments
129
Opportunity sampling disadvantages
- unrepresentative
| - self selection
130
Random Sampling
A sample of participants produced by using a random technique so that every member of the target population has an equal chance of being selected.
131
Random Sampling advantages
- unbiased selection
| - generalisation
132
Random sampling disadvantages
- impractical
| - not representative
133
Volunteer Sampling
A sample of participants produced by a sampling technique that relies solely on inviting people to take part.
134
Volunteer sampling advantages
- ease of formation
| - less chance of screw u phenomenon
135
Volunteer sampling disadvantages
- unrepresentative
| - demand characteristics
136
Systematic Sampling
Involves taking every nth person from a list to create a sample
137
Systematic sampling advantages
- unbiased selection
| - generalisation
138
Measures of Dispersion
The general term for any measure of the spread or variation in a set of scores.
139
Descriptive Statistics
The use of graphs tables and summary statistics to identify trends and analyse sets of data.
140
Pilot Study
A small scale trial carried out at the start of an experiment to check for any flaws e.g. do the questions in the questionnaire make sense.
141
Mean
The arithmetic average. Calculated by adding up all of the values in a set of data and dividing by the number of values.
142
Evaluation of The Mean
+ Most sensitive of the measures of central tendency as it includes all data
+ More representative
- Easily distorted with extreme values therefore won't be representative
143
Median
The central value in a set of data when it is ordered from lowest to highest value.
144
Evaluation of The Median
+ Extreme scores don't have an effect
+ Easy to calculate
- Not very sensitive as not all scores are included
145
Mode
The value that appears most frequently in a set of data
146
Evaluation of The Mode
+ Very easy to calculate
+ For data in categories it's the only appropriate measure
- Crude measure as the mean and mode can be very different
- Not representative
147
What measure of central tendency to use
Mean - If there are NO extreme values (most sensitive)
Median - If there are extreme values (the mean would be distorted)
Mode - Only if the data is in catogries
148
Thematic analysis
a method of qualitative research linked to content analysis, which involves analyzing data to identify the patterns within it
149
Thematic analysis stages
1. familiarisation with the data
2. coding
3. search for themes
4. reviewing themes
5. defining and naming themes
6. writing up
150
Range
Calculation of the dispersion in a set of scores. Worked out by minusing the lowest value from the highest value and adding one as a mathematical correction.
151
Evaluation of The Range
+ Easy to calculate
- Only uses the 2 most extreme scores which may be unrepresentative of all the data
- May not give a fair representation of the general spread of scores
152
Standard Deviation
How far scores deviate from the mean
153
Evaluation of Standard Deviation
+ More precise than the range as it includes all values with in the final calculation
- Can be easily distorted by an extreme value e.g. the mean
154
Types of graphs
Bar Chart
Scattergram
Histogram
Line graph
155
What to include on a graph
Title showing a relationship between the co-variables
Labelled X and Y axis
Accurately plotted data
156
Bar Charts
Used when data is divided into categories (discrete data)
The bars are separated to show different categories
157
Histograms
Used when data is continuous
The bars touch each other
158
Line Graphs
Represent continuous data
Each point is connected by a line
Usually the IV is plotted on the X axis and the DV is plotted on the Y axis
159
Normal Distribution
There is a symmetrical spread of frequency data that forms a bell shaped pattern
160
Characteristics of a normal distribution
Its bell shaped
Its symmetrical
The mean, median, mode are all in the centre
The 2 tails never touch the horizontal axis
161
Positively Skewed Distribution
| Right Skewed
The long tail is on the positive side of the peak and most of the distribution is centred to the left.
162
Negatively Skewed Distribution
| Left Skewed
The long tail is on the negative side of the peak and most of the distribution is concentrated on the right.
163
Skewed Distributions
When the spread of data is not symmetrical meaning the data clusters to one end.
The mode is located at the highest point, then the median and finally the mean.
164
Statistical Testing
We need to know if the results are significant i.e. are the results strong enough to reject the null hypothesis and accept the research hypothesis.
The difference may be due to chance or coincidence.
165
The sign test
Involves counting up the number of positive snd negative signs.
To use the sign test we need to:
be looking for differences not associations
have used a repeated measures design
have data which is organised into categories (nominal)
166
Accepted level of probability
In psychology the accepted level is 0.05 / 5%
Sometime researchers need more confidence so have a more stringent significance level of 0.01 / 1% e.g. when humans lives are involved.
167
Calculated Value
The number the researcher is left with after the statistical test has been calculated. It is compared to the critical value to see whether the results are significant.
168
Critical Value
The critical values table is given to you.
To use the critical values you need to know:
1) Desired significance level (usually 0.05)
2) The number (N) of participants
3) Whether the hypothesis is directional or non-directional
169
Significant Results
The results are significant if the calculated value is equal to or lower than the critical value.
170
How to carry out the sign test
1) Convert data into nominal data by subtracting one condition away from the other. If the number is negative you put a - sign and if it is positive you put a + sign in the sign of difference column
2) Add up the number of + & - signs (if p.ps got the same score in both conditions their data is ignored)
3) Take the less frequent sign and call this 'S' which id the calculated value
4) Compare the calculated value to the critical value (the calculated value needs to be equal to or less than the critical value).
5) Write up the sign test
171
What to include in the sign test write up
The relationship between the calculated and critical value
How many participants there were
The significance level
Whether it was one tailed or two tailed
If its significant or not.
172
Systematic sampling disadvantage
- periodic traits
| - not representative
173
Stratified sampling advantages
- representative
| - unbiased
174
Stratified sampling disadvantages
- knowledge of population characteristics required
| - time consuming
175
Pie charts
Used to show the frequency of categories as percentages
176
Stratified Sampling
A sampling technique where groups of participants are selected in proportion to their frequency in the population in order to obtain a representative sample.
177
Confidentiality/anonymity
Participants data should not be disclosed to anyone unless agreed in advance
178
Correlation
A mathematical technique, where a researcher investigates an association between two variables call co-variables.
179
Positive Correlation
As one variable increase the other variable increases.
180
Negative Correlation
as one variable increases, the other decreases
181
Co-Variables
The variables investigated within a correlation e.g. height a weight.
182
Zero Correlation
When there is no relationship between the co-variables.
183
Statement for the sign test?
Used when we are looking for a Difference, using
Related measures design ( repeated or matched pairs) with Nominal
level data.
184
Statement for Chi Squared?
+ solution
Justification - Used when we are look for a Difference, using
Independent measures design with Nominal level data.
calc the df + 1 tailed/ 2 tailed
185
Statement for the Mann Whitney U test?
+ solution
Used when we are looking for a difference using independent measures when we have at least ordinal level data.
Na and Nb
186
Statement for the Wilcoxon T test?
+ solution
Wilcox T test is used when you are
looking for a difference using a repeated measures or
matched pairs ( related measures) design with data
that is at least ordinal.
N p/pants + 1/2 tailed
187
Statement for Related T test?
+ solution
Used when looking for a difference, using a related
measures design with data of interval level data which is parametric.
N -1 = df
188
Statement for Unrelated T test?
+ solution
Used when looking for a difference, using a unrelated
measures design with data of interval level data.
Na + Nb -2 (un) =df
189
How do you write a reference?
Author A. A. (Year). Title of the article. Name of the Periodical, volume(issue), #-#, link
190
Statement for Pearson's R?
+solution
Use Pearson's R when you have a correlations study
which has interval level data that is Parametric.
N + 1/2 tailed tests
191
Statement Spearman's Rho?
+solution
Use a Spearman's Rho when you have a correlations study which has
at least ordinal level data.
N + 1/2 tailed test
AQA Psychology
flashcards
Decks in class (5)
# Cards
