Research Methods - Need to do booklet 3 Flashcards
1
Q
What are the key features of an experiment?
A
- Investigates the difference between two conditions
- Manipulation and measurement of variables
- To test a hypothesis
- To establish ‘cause and effect’
2
Q
What is a purpose of an aim?
A
- To identify what variables the study is investigating
- To explain the outline and purpose of the study
3
Q
What is the independent variable?
A
What the researcher manipulates in the experiment
4
Q
What is the dependant variable?
A
What the researchers measures in the experiment
5
Q
What is an experimental hypothesis?
A
A prediction about the expected outcome of an experiment. It is wrote as a precise and testable statement.
6
Q
What is a null hypothesis?
A
- This is the hypothesis the researcher is trying to disprove
- It states that the results will not be significant in terms of supporting the idea being investigated
7
Q
What is operationalisation?
A
Describing the variables in terms of how they will be precisely manipulated and measured
8
Q
What are the two experimental hypothesis?
A
- Directional
- Non directional
9
Q
What is a directional hypothesis also known as?
A
One tailed
10
Q
What is a directional hypothesis?
A
The hypothesis specifically states the direction of the results
11
Q
When is a directional hypothesis usually used?
A
When previous/past research has shown a particular outcome is likely
12
Q
What is a non directional hypothesis also known as?
A
Two tailed
13
Q
What is a non directional hypothesis?
A
The hypothesis does not specify the expected directional of the results
14
Q
When is a non directional hypothesis used?
A
When there is little or previous research
15
Q
What are the key features of Laboratory experiments?
A
- Controlled in a tightly, controlled, artificial environment
- Experimenter deliberately manipulates the independent variables
-Experimenter measures the dependant - Attempt to control/minimise other variables that could effect dv
- Standardised procedure
16
Q
What are the key features of field experiments?
A
- Conducted in a natural, real world environment
- Experimenter deliberately manipulates the IV
- Experimenter measures DV
- There is minimal control of other variables that can affect DV
17
Q
What are the key features of natural experiments?
A
- Can be conducted in any setting
- IV is naturally occurring
- The IV is an event/experience
- Experimenter measures DV
- Little/no control of other variables
18
Q
What are the key features of Quasi experiments?
A
- Can be conducted in any setting
- IV is naturally occuring
- IV is a pre-existing characteristic (age, gender etc)
- Experimenter measures the DV
- Has little or no control over other variables that could affect DV
19
Q
What does standardisation mean?
A
Procedures and conditions being controlled and kept the same across all conditions allowing for replication
20
Q
What does ecological validity mean?
A
The extent to which the experimental setting represents real life situations and behaviour
21
Q
What does demand characteristics mean?
A
Behaviour from participants in the experimental setting which may be unnatural and affect how they perform on tasks
22
Q
What does validity mean?
A
The extent to which an experiment is accurate in measuring what it claims to measure
23
Q
What does mundane realism mean?
A
The extent to which the tasks used in the experiment are representative of tasks completed in everyday life.
24
Q
What does reliability mean?
A
The extent to which an experiment can be repeated to check the consistency of the results
25
What does internal validity mean?
The extent to which there is confidence in the IV causing an effect on the DV
26
What are the advantages of lab experiments?
- High internal validity (EVs controlled)
- High reliability (standardised procedure)
27
What are the disadvantages of lab experiment
- Low ecological validity and mundane realism (artificial tasks)
- High demand characteristics (P's aware taking part in experiment)
28
What are the strengths of field experiments?
- High ecological validity and mundane realism (real life tasks)
- Low demand characteristics (P's usually unaware they are taking part)
29
What are the weaknesses of field experiments?
- Low internal validity (Hard to control EVs)
- Low reliability (hard to standardise)
30
What are the advantages of natural and quasi experiments?
- Can study sensitive research questions (allows investigation of variables that would be harmful to manipulate)
- High mundane realism and ecological validity (everyday tasks)
31
What are the disadvantages of natural and quasi experiments?
- Low internal validity (IV not manipulated directly)
- Low reliability (naturally occurring IV and hard to standardised)
32
What is an extraneous variable?
A variable, other than the IV, that may affect the DV if it is not controlled
33
What is a confounding variable?
- A type of extraneous variable
- It is one that systematically changes alongside the IV
- Means It is possible it has caused a change to the DV
34
What is situational variables?
Features of the environment/ setting that might affect participants behaviour
35
How can you control situational variables?
Standardisation of all procedures
36
What are participant variables?
Individual differences between participants and the ways in which each participant varies from the other
37
How can you control participant variables?
Randomisation of participants to conditions
38
How can demand characteristics be controlled?
- Using some deception: not revealing true aim of study
- Double blind procedures: neither participant or researcher are aware of which conditions they've been assigned too
39
What is an investigator effect?
Any (unintentional or unconscious) unwanted influence of the researcher's behaviour/characteristics on the participant's data/outcome
40
How can investigator effect be controlled?
- Using the same researcher for all participants
- Double blind procedures
41
What does experimental designs mean?
How researchers are going to allocate and organise participants into conditions of an experiment
42
What are the three experimental designs?
- Repeated measures
- Independent groups
- Matched pairs
43
What is a repeated measures design?
Each participant does both conditions of an IV
44
What are the strengths of repeated measures design?
- Participant variables are controlled for
45
What are the disadvantages of repeated measures design?
- Demand characteristics likely to be experienced (become aware of what's being manipulated)
- Order effects likely to be experienced
46
How can order effects be prevented in repeated measures design?
Counterbalancing, some do condition A and then B and vice versa
AB - BA
47
What is independent groups design?
Each participant does one condition of the IV - split equally
48
What are the advantages of independent groups design?
- Less chance of demand characteristics (only do one condition)
- Less chance of order effects (Only do one condition)
49
What are the disadvantages of independent groups design?
- Participant variables not controlled for
50
What is matched pairs design?
- Each participant is put into pairs by being matched on important variables (IQ, gender, age etc
- Each pair is split up into a condition (one in condition A and the other in condition B)
51
What is an advantage of matched pairs design?
- Less chance of demand characteristics and order effects
52
What is a disadvantage of matched pairs design?
Difficult to achieve
53
What does probability mean?
Refers to how sure that our results from an investigation are really significant and have not occurred by chance
54
What does a big probability mean in psychology?
- Bad
- More likely that the results have occurred by chance
55
What does a small probability mean in psychology?
- Good
- We can be confident that the results were not due to chance and are significant
56
How does psychologists calculate the probability of results being due to chance?
Statistical tests
57
What are the 8 statistical tests?
- Unrelated T-test
- Chi square
- Mann Whitney
- Related T-test
- Sign test
- Spearman's Rho
- Pearsons r
- Wilcoxon
58
What probability do we use in psychology?
P is less than or equal to 0.05
59
What does P is less than or equal to 0.05 mean?
95% sure that the results are significant
60
What is the stringent level?
P is less than or equal to 0.01
61
When is stringent levels used?
If we need to be more confident than accepting a 5% probability the results are due to chance
62
What is the non-stringent level?
P is less than or equal to 0.1
63
When is non-stringent level used?
If we only need to demonstrate an effect/difference/relationship
64
What is a type 1 error also known as?
False positive
65
What is a type 1 error
Wrongly accepting the experimental hypothesis when the null should be accepted
66
When does a type 1 error occur?
With a non-stringent level
67
What is a type 2 error also known as?
False negative
68
What is a type 2 error?
Wrongly accepting the null hypothesis when the experimental hypothesis should be accepted
69
When does a type 2 error occur?
With the stringent level
70
How do you remember statistical tests?
- NOI (left down)
- RIC (Top row)
- Simon Cowell Wants More Singers Receiving Unanimous Praise (centre left to right)
71
What is the calculated/observed value in statistical tests?
The number produced after the statistical test has been calculated
72
What is the critical value table in statistical tests?
A value taken from a statistical test table which must be reached in order for results to be significant
73
How do you calculate a sign test?
- Calculate the difference between each participants two scores and note wether difference + or -
- Add up number of times + and - occurs
- The sign (+ or - ) that occurs less frequently is the calculated value and is known as 's'
- Calculate number of participants
- Interpret the significance.
74
When is a sign test significant?
The calculated value of S must be less than or equal to the critical value to be significant
75
When is a wilcoxon test significant?
The calculated value of T must be equal too or less than the critical value to be significant
76
When is a Mann Whitney test significant?
The calculated value of U must be equal to or less than the critical value to be significant
77
How do you calculate the df in a chi square experiment?
(number of rows - 1) x (number of columns - 1)
78
When is a chi-squared test significant?
The calculated value of chi must be greater than or equal to the critical value to be significant
79
When is a spearmans rho test significant?
The calculated value of rho must be equal too or more than the critical value to be significant
80
When is a Pearsons R test significant?
The calculated value of r must be equal too or more than the critical value to be significant
81
When is a unrelated T-test significant?
The calculated value of t must be equal to or more than the critical value to be significant
82
When is a related T-test significant?
The calculated value of t must be equal to or more than the critical value to be significant
83
How do you calculate the df in a related T-test?
N - 1
84
How do you calculate the df in a unrelated T-test
Na + Nb - 2
85
What is a target population?
The group of people who the researchers want to generalise (apply) their results too
86
What is a sample?
A small number of people taken from the target population who participated in the investigation
87
What is sampling bias?
When the sample selected under or over represent certain groups that compose the target population
88
What is random sampling?
- Where every participant in the target population has an equal chance of being selected through a lottery system,
- No bias from the psychologist
- Those selected are then contacted and invited to participant
89
What is an advantage of random sampling?
- Likely to be representative of the target population
90
What is an disadvantage of random sampling?
- Time consuming and inconvenient
91
What is opportunity sampling?
Approaching and inviting those who are available
92
What is an advantage of opportunity sampling?
More convenient to use
93
What is a disadvantage of opportunity sampling?
Unlikely to be representative of target population?
94
What is volunteer sampling?
- The sample is self selected
- Involves adverting the study and providing contact details so that individuals respond if they wish to participate in the study
95
What are the advantages of volunteer sampling?
More convenient
96
What are the disadvantages of volunteer sampling?
Unlikely to be representative of target population
97
What is systematic sampling?
- Involves devising a sampling frame and a system being nominated to select every Nth person.
- Those selected will be contacted and invited to participate
98
What is an advantage of systematic sampling?
Representative of target population
99
What is a disadvantage of systematic sampling?
Still possible to be unrepresentative of target population
100
What is stratified sampling?
- Identifying groups call strata that exist in the target population
- Calculating the proportions of individuals needed from each strata to represent the overall target population
101
What is an advantage of stratified sampling?
Very representative of target population
102
What is a disadvantage of stratified sampling?
Very time-consuming and inconvenient to use
103
What are the key features of a correlation?
- Measures the relationship between two co-variables
- Direction of the relationship can be negative or positive
- Strengh of correlation can be strong, moderate or weak
- Can be represented as a correlation coefficient
- Can be represented as a scattergram
- Can be used to measure reliability
104
What is a positive correlation?
As scores on one variable increase so do scores on the other variable
105
What is a negative correlation?
As scores on one variable increases, scores on the other variables decreases
106
What is a zero correlation?
No relationship between two variables
107
What are used to display the findings of correlations?
Scattergrams
108
What is a correlation coefficient?
- A more accurate way to indicate the strength of a correlation
- Closer to 1 = stronger it is
109
What are the advantages of correlations
- Useful preliminary tool for further research
- Allow the study of variables which cannot be manipulated in experiments
110
What is a disadvantage of correlations?
Can only establish a relationship between variables
111
What is quantitive data?
Numerical data consisting of participants scores or numbers of some sort
112
What is qualitative data?
Descriptive data expressed in the form of written thoughts, feelings and opinions
113
What is the advantage of quantitive data?
- It is objective
- So it can be mathematically analysed
114
What's the disadvantage of quantitive data?
- Doesn't consider a participants emotions and feelings
- Lacks insight into the reasons behind human behaviour
115
What is the advantage of qualitative data?
- Has more detail allows for thoughts and feelings
- Gives meaningful insight so its high in external validity
116
What is the disadvantage of qualitative data?
- Comparisons hard to make as it is not easy to analyse
- Conclusions are based on subjective interpretations
117
What is primary data?
Data which is collected by a researcher first-hand and is gathered directly from the participants themselves
118
What is secondary data?
Data collected from participants from other people and already exists
119
What is an advantage of primary data?
- It is authentic as its collected first hand
120
What is a disadvantage of primary data?
Can be time consuming
121
What is an advantage of secondary data?
It is easily accessible and requires minimal effort to collect
122
What is a disadvantage of secondary data?
- Content may not meet the researchers need
- Could lack valuable information
- Content may be out of date
123
What is meta analysis?
- When a researcher combines the findings from a number of previously published studies
- Studies all deal with the same research question
- It produces a statistic to represent the average
124
What is an advantage of meta-analysis
- Has greater statistical power
- Has more ability to generalise findings to a wider population
- Considered to be evidence based
125
What is a disadvantage of meta-analysis?
- Can be difficult and time consuming
- Requires complex statistical skills and techniques
126
What type of data does levels of measurement relate too?
Quantitive data
127
What is nominal data?
A frequency count for distinct categories where something can only belong to one category
128
What level of measurement is the most basic and least informative?
nominal data
129
What is ordinal data?
Where numbers can be ordered in some way such as a questionnaire
130
What level of measurement is more informative than nominal
ordinal
131
What is interval data?
measurements taken from a numerical scale where each unit is the same size and the gap between each unit is fixed and equal
132
What level of measurement is the most sophisticated and precise?
Interval
133
What statistics is a way of presenting and summarising quantitive data?
Descriptive data
134
What is measures of central tendency?
Information about the 'typical' value (averages)
135
What are examples of measures of central tendency?
Mean, median, mode
136
What are measures of dispersion?
Information about how 'spread' out the values are (variability)
137
What are examples of measures of dispersion?
Range and standard deviation
138
What are the two types of descriptive statistics?
- Measures of central tendency
- Measures of dispersion
139
What is a mean?
Statistical average for a set of data
140
What levels of measurement is a mean suitable for?
Ordinal and interval
141
What is a advantage of using a mean?
- Most sensitive measure of central tendency
- This is because it includes all scores
- So it is the most representative measure
142
What is a disadvantage of using a mean?
- Easily distorted by extreme values
- So may not be representative
143
What is a median?
Central half way value of a set of data
144
What level of measurement is a median suitable for?
Ordinal and interval
145
What is the advantage of using a median?
- Not affected by extreme values so useful when mean not appropiate
- Easier to calculate than mean
146
What is the disadvantage of using a median?
- Not as sensitive as the mean as does not include all scores in a set of data
147
What is the mode?
The value that occurs most often
148
What levels of measurement is a mode suitable for?
All levels (nominal, ordinal, interval)
149
What is a advantage of a mode?
- Easiest to calculate
- Unaffected by extreme values
- Only measure of central tendency nominal data can be used with
150
What is a disadvantage of a mode?
- Crude measures so can be unrepresentative in small data sets
- Less useful when there are several modes in a data set
151
What is a range?
The differences between the highest and lowest values
152
What is the advantage of using a range?
Easiest measure of dispersion to calculate
153
What is the disadvantage of using a range?
- Only takes into account the two most extreme values
- This makes it unrepresentative of the data set
154
What is standard deviation?
Describes how much, on average, all values differs from the mean
155
What does a large standard deviation score mean?
That there is a lot of variation from the mean
156
What does a small standard deviation score mean?
- Tells us there is not a lot of variation from the mean
- The SD would be close to 0
157
What is a advantage of standard deviation?
It is a sensitive and precise measure of dispersion as all the values in a data set are taken into account when calculating it
158
What is a disadvantage of standard deviation?
- Doesn't tell you the full range of the data
- Can be affected by extreme scores to give a skewed picture
159
What do tables provide?
A summary of the raw scores covered to descriptive statistics
160
What do graphs provide?
A visual representation of a set of data which allows us to see the patterns in a easy to understand way.
161
What are the key features of a bar chart?
- Used to make a comparison between scores
- Used with categories of data
- Bars are always separate
162
What are the key features of a scattergram?
- Used to show a relationship between two variables
- A line of best fit may be drawn through the plots
163
What are the key features of histograms?
- Illustrate the frequency of data items
- Used with continuous data, such as test scores
- Bars always touch
164
What are key features of a line graph?
- Illustrate continuous data
- Show how something changes in value, such as over time
- DV plotted on Y- Axis
- IV plotted on X - Axis
165
What are the key features of a pie chart?
- Used with discrete data
- Each segment of the circle represents a proportion of the scores
166
What does a normal distribution curve display?
Displays frequency data on a variable of interest
167
What shape does a normal distribution have?
Symmetrical bell curve
168
Where are the mean, median, mode located on a normal distribution?
Located on the highest peak
169
What is a skewed distribution?
When scores are clustered to one side (left or right) of the mean
170
What does a positive skew look like?
- Long tail on the right
- From left to right: Mode, Median, Mean
171
Where does a large amount of data fall in a positive skew?
Below the mean score
172
What does a negative skew look like?
- Long tail on the left
- From left to right: Mean, Median, Mode
173
What do observations involve?
The systematic measurement of freely occurring behaviour
174
What are the key features of observational techniques?
- Record of actual behaviour rather than participant thoughts
- It is a research method in its own right
- Types of observation include features regarding: location, participant awareness, involvement of researcher
175
What does location observation refer to?
Where the observation is conducted
176
What are the two types of location observation?
- Naturalistic
- Controlled
177
What is naturalistic observation?
- Participants are observed in their natural environment
- Everything has been left as it normally would be
- The observation is in the participants normal place of activity
178
What is controlled observation?
- Participant are observed in an artificial and contrived environment where there has been some creation of a 'set up'
- This is often a laboratory but doesn't have to be, it can be anywhere the researcher has some regulation
179
What does overt and covert observation refer too?
Whether participants have consented to/are aware they are being observed
180
What is overt observation?
- The participants know they are being observed and informed consent is given beforehand
- The researcher may be visible but researchers try to be as unobtrusive as possible
- May use one way mirrors so they are hidden from view
181
What is covert observation?
- Participants are not aware they are being watched and so have no given consent beforehand or during the observation
- Participants are often being observed from researchers who are undercover
- To avoid ethical issues, covert observations should be done in an public place and participants should be debriefed afterwards if possible
182
What does participant and non-participant observation refer too?
The researchers level of involvement
183
What is non-participant observation?
- The researcher remains separate from those being observed and is a bystander
- There is little/no interaction with participants
- Most observations in psychology are non participant
184
What is participant observation?
- The researcher participates in the behaviour being observed and becomes part of the group being observed
- The researcher may take a false identity and role posing as a genuine member of the group
- These are very rare in psychology
185
What is the design of unstructured observation?
- Researcher freely records all relevant behaviour, usually in note form, without imposing a system on what is being observed
- May be used in situations where no research exists and so acts as a pilot study
186
What is the design of structured observation?
- Used more commonly in psychology
- A system is imposed before an observation happens which involves cater goring what behaviour is to be observed and devising a sampling procedure
- Likely to be video recorded
187
What type of data does structured observation produce?
Quantitive data
188
What are behavioural categories?
- Used in structured observations
- The behaviour being studied is broken down into behavioural categories
- This is a form of operationalising general behaviour into specific, objective and measurable set components
189
What are the two types of behaviour sampling?
- Event
- Time
190
What is event sampling?
- Observers record every time a certain behaviour occurs and counts the frequency of the behaviour
191
When is event sampling best?
If researchers don't want to miss any behaviours
192
What is a limitation of event sampling?
It is difficult if there is lots of behaviour
193
What is time sampling?
Observers decide on a time interval and record which behaviour happens at that time
194
When is time sampling best?
If there are lots of behaviours that likely occur often
195
What is a limitation of time sampling?
Behaviours may be missed
196
What does reliability in observations refer too?
Consistency
197
What should observations do to improve reliability?
- Use clear, distinct and precisely defined behavioural categories
- Ensure there is more than one observer present and/or video record observation
- Ensure observers train together to check how behaviour is recorded
198
How can we check reliability in observations?
Inter-observer reliability
199
What is inter-observer reliability?
- A second observer is used and coding of the observation is done separately by the two researchers
- A comparison of the two observers' coding will be made after the observation is complete to see whether the analysis has given similar results
- A correlational analysis will be performed, if the coding is similar the co-efficient is above 0.8
200
What are some general strengths of observations?
- Can have high ecological validity
- Can be low in demand characteristics
201
What are some general weaknesses of observations?
- Can have low internal validity
- Observations can be affected by observer bias more than experimental methods
202
What are strengths of naturalistic observations?
- High ecological validity
- Often used to generate new ideas
203
What are the weaknesses of naturalistic observations?
- Often on a small scale (lacks generalisability)
- Other variables cannot be controlled
- Needs training of observer to do it
- No manipulation of variables
204
What are the strengths of controlled observations?
- Can be easily replicated
- Easier and quicker to analyse as uses quantitive data
- Fairly quick to conduct so can gain a large sample which is more generalisable
205
What are the weaknesses of controlled observations?
- Can lack validity due to demand characteristics
206
What are the strengths of overt observation?
No ethical issues
207
What are the weaknesses of overt observation?
Behaviour may not be natural
208
What are the weaknesses of covert observations?
High ecological validity
209
What are the strengths of covert observations?
Ethical issues
210
What are the strengths of participant observation?
- Easier to understand the observers behaviour
- High ecological validity
211
What are the weaknesses of participant observation?
- Can be hard to get time or privacy to record information
- If they get too involved they may lose objectivity
212
What are the strengths of non-participant observation?
- Observations made as they happen which is reliable
- Lack of contact so the observer can maintain objectivity
213
What are the weaknesses of non-participant observation?
- Behaviour may be recorded but the meaning behind it may be unknown
214
What does self report mean?
Participants directly reveal information about themselves, without researcher interference
215
What do self-report techniques investigate?
Participants beliefs, thoughts and feelings through asking them a series of questions
216
What are the two main types of self-report techniques?
- Questionnaires
- Interviews
217
What are the key features of questionnaires?
- Are a set of written questions
- Questions are predetermined
- Questions can be closed or open-ended
- Questionnaires can be done in person, post, online, over the phone
218
What is an open ended question?
A question which doesn't require a fixed response
219
What type of data does a open ended question produce?
Qualitative
220
What is a close ended question?
It gives the participant a fixed response option to choose one answer from a small selection of alternatives
221
What type of data does a closed ended question produce?
Quantitive
222
Why do questionnaires and interviews need to be designed carefully?
To avoid social desirability, bias and low response rate
223
When designing a questionnaire, what should you consider?
- Aims
- Question style, order and length
- Question information
- Ethical issues
224
What are the advantages of questionnaires?
- Less time consuming (you can email or post them and no researcher needed)
- People tend to be more honest with their answers (because people can do it privately)
225
What are the disadvantages of questionnaires?
- Likely to produce bias
- Less detailed to interviews (often closed questions)
226
What are the two types of bias questionnaires can produce?
- Response - people may rush or don't fully read questions
- Social desirability - people may be untruthful
227
What are the key features of an interview
- Involves asking participants questions more naturally in a FTF situation
- Can use closed and open questions, but mostly open
- Can be structured or unstructured
228
What are structured interviews?
- The interviewer has a topic to explore with the respondent that has a set of predetermined questions
- Each interviewee is asked the same questions and they are not deviated from
229
What should you consider when designing a interview
- Recording of the interview
- The effect of the interviewer
- Questioning skills
- Ethical issues
230
What are the advantages of interviews?
- More detailed to questionnaires
- They allow the opportunity to clarify misunderstandings
231
What are the disadvantages of interviews?
- May be problems with investigator effects
- They are more time consuming compared to questionares
232
What is a case study?
It is an in depth investigation of either a single person, a group of people, an event or an institution
233
What are the key features of case studies?
- The subject is often rare or unusual
- Researchers construct a case history by gaining information using a range of different research methods
- The information collected is mostly qualitative but can be quantitive
- Tend to be longitudinal (subject follow fro a long time)
- Some case studies are retrospective
234
What the advantages of case studies?
- Allow investigation into areas that are otherwise unethical or unpractical
- Provide insight for future research areas
235
What are the disadvantages of case studies?
- Can be highly subjective
- Unrepresentative and unreliable
236
What are the two methods to analyse qualitative data?
- Content analysis
- Thematic analysis
237
What are the key features of content analysis?
- A form of indirect observation, it is analysis of individuals communication
- It is conducted in a systematic way, which devises categories and coding units
- It converts qualitative data to quantitive
238
What does content analysis consider?
- Manifest content: what the text seems to be about
- Latent content: What the text is really about
239
What is the process of conducting content analysis?
- Come up with an aim of hypothesis
- Select a sample you will conduct the analysis on (book, magazine etc)
- Create coding units of behaviour
- Go through the sample and record any instances of the coding unit
- The total number of each coding unit is counted to create quantitive data
240
What are the key features of thematic analysis?
- Involves coding and indemnifying patterns and themes
- Themes are analysed and used to support or challenge theories with specific examples of quotes
- Keeps the data in qualitative form
241
What is the process of thematic analysis?
- Familiarise yourself with the data
- Produce coding units
- Look for emerging themes
- Define and name each separate theme
- Write up report
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What are the similarities between content and thematic analysis?
- Both involve qualitative data
- Both involve the coding of information
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What are the differences between content and thematic analysis?
- Content analysis collects quantitive data but thematic collects qualitative
- Themes emerge in thematic whereas coding units are predetermined in content
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What are the strengths of qualitative analysis?
- Statistical analysis of data becomes possible in content analysis (More problematic in thematic)
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What are the weaknesses of qualitative analysis?
- Content analysis can be argued to be a reductionist technique (less problematic in thematic)
- Researchers subjective opinions may influence content analysis (more problematic in thematic)
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What is a pilot study
- A small scale preliminary investigation with fewer participants
- The results are not published
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What is the purpose of a pilot study?
To assess any unexpected problems and allow amendments to be made before the main study
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What do pilot studies for an experiment check?
- Do participants understand the instructions
- Do participants understand the task
- Is the time to do the task to long or short
- Are the tasks appropriate
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What do pilot studies for an observation check?
- Are the behavioural categories suitable, objective, operationalised
- Are there enough examples of behavioural categories
- Is the sampling used appropriate
- Is the location appropriate
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What do pilot studies for a self-report check?
- Are the questions in the self report methods clear, not too complicated, unambiguous
- Are the responses appropriate and answerable in close ended questions
- Are there any unanswered questions and if so why
- If any ethical issues are raised with the questions being asked
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What is the definition of reliability?
Refers to the consistency of the test/measurement/researcg
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What does reliability refer too?
How well research can be replicated at another time and/or by other researchers
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When is a test considered reliable?
If the same results are repeatedly found
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What are the two ways of assessing reliability?
- Test retest
- Inter observer(rater) method
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What is the test-retest method?
- Where a test/questionare/interview is administered on at least two occasions with a reasonable time gap to the same sample of participants
-Two indépendant sets of scores are therefore created which are then compared
- If similar results are produced each then it is reliable
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What is the inter-observer (rater) method?
