Research Methods Flashcards
1
Q
Population
A
A group of people who are the focus of the researcher’s interests, from which a smaller sample is drawn
2
Q
Sample
A
A group of people who take part in a research investigation. The sample is drawn from a target investigation and is presumed to be representative of the population, i.e. it stands ‘fairly’ for the population being studied
3
Q
What is a Sampling techniques
A
The method used to select people from the population
4
Q
Bias in sampling
A
In the context of sampling, when certain groups are over-or under-represented within the sample selected. For instance, there may be too many younger people or too many people of one ethnic origin in a sample. This limits the extent of which generalizations can be make to the target population
5
Q
Generalization
A
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 representative of the target population
6
Q
What is an experimental method
A
Involves the manipulation of an IV to measure the effect on the DV
7
Q
Types of experimental methods
A
- lab
- field
- natural
- quasi
8
Q
What is the aim
A
A general statement of what the researcher intends to investigate
The purpose of the study
9
Q
What is a hypothesis
A
A clear, precise, testable statement that states the relationship between the variables to be investigated
- stated at the outset of any study
10
Q
What are the types of hypotheses
A
- experimental
- alternative
- directional
- non-directional
11
Q
What is a directional hypothesis
A
States the direction of the difference of relationship
- states how the IV will effect the DV
- only use if there is enough background research to predict the results
12
Q
What is a non-directional hypothesis
A
Does not state the direction of the difference of relationship
- will only say that there will be a difference
13
Q
What is an experimental hypothesis
A
When an experimental method will be used
14
Q
What is an alternative hypothesis
A
When a non-experimental method will be used
- observation
15
Q
What is the general formula for writing a hypothesis
A
There will be a significant difference in (DV) between (IV CONDITION 1) and (IV CONDITION 2)
16
Q
Why do you need both a hypothesis and a null hypothesis
A
So that at the end you are able to accept and reject one
17
Q
Why do you operationalize the variables in a hypothesis
A
- usually what is being tested in not easy to define
- operationalizing variables allows them to be as measurable as possible
- give exact values
18
Q
What is an independent variable
A
The part of the investigation that is manipulated by the researcher so that the effect on the DV can be measured
19
Q
What is the dependant variable
A
The variable that is being measured by the researcher
- an effect of the DV should be caused by the change in the IV
20
Q
What is operationalisation
A
Clearly defining variables in terms of how they can be measured
21
Q
What is the formula for a null hypothesis
A
There will be no significant difference in the (DV) between the (2 IVs), and that any difference seen is DUE TO CHANCE
22
Q
What are extraneous variables
A
Any variable, other than the IV, that may effect the DV if it is not controlled
23
Q
What is a confounding variable
A
A kind of EV that varies systematically with the IV
- if there is a change in the DV it is due to the IV or confounding variable
24
Q
What are demand characteristics
A
Any cue from the researcher/ research situation that may be interpreted by participants as revealing the purpose of the investigation
- may lead to participants changing their behavior
25
What are investigator effects
Any effect of the investigator’s behavior of the research outcome
- anything from the design of the study
- to the interaction with the participants
26
What is randomization
The use of chance methods to control for the effects of bias when designing materials and deciding the order of experimental conditions
27
What is standardization
Using exactly the same formalised procedures and instructions for all participants in a research study
28
What are the two types of extraneous variables
- participant variables
- situational variables
29
What are participant variables
Any individual differences between participants that may effect the DV
- age
- personality
- gender
30
What are situational variables
Any features of the experimental situation that may effect the DV
- noise
- time of day
- weather
31
What is a pilot study
A small-scale version of an investigation that takes place before the real investigation happens
- check that procedures, materials, measurements work
- allow the researcher to make changes or modifications if necessary (method or procedure)
- uses a smaller sample group that would actually be used in the real investigation (target population)
- NOT carried out to test ethical issues
- pilot study must be ethical before being carried out
32
What is a single blind procedure
Any information that might create expectations is not revealed into the end of the study to control for the confounding effects of demand characteristics
33
What is a double blind procedure
Neither the participants nor the researcher who conducts the study is aware of the aims of the investigation
34
What is a control group
Allows you to set a base line for the investigation
- comparison
35
What is an experimental design
The different ways in which participants can be organized in relation to the experimental conditions
36
What are the different types of experimental designs
- independent group
- repeated measures
- matched pairs
37
What is an independent group design
- when two separate groups of participants experience two different conditions of the experiment
- one group in the experimental group and the other is the control group
38
What is repeated measures
All participants take part in all conditions of the experiment
39
What is the matched pairs design
Pairs of participants are first matched on some variables that may effect the DV
- one member of the pair is assigned to condition A and the other to condition B
40
What is random allocation
An attempt to control for participant variables in an independent groups design which ensures that each participant has the same chance of being in one condition as any other
41
What is counterbalancing
An attempt to control for the effects of order in a repeated measures design
- half the participants experience the conditions in one order and the other half in the opposite order
42
What is a lab experiment
An experiment that takes place in a controlled environment within which the researcher manipulates the IV and records the effect on the DV, which maintaining strict control of extraneous variables
43
What is field experiments
An experiment that takes place in a natural setting within which the researcher manipulates the IV and records the effect on the DV
44
What are natural experiments
An experiment where the change in the IV is not brought about by the researcher but would have happened even if the researcher had not been there. The researcher records the effects on a DV they have decided on
45
What is a quasi-experiment
A study that is almost an experiment but lacks bey ingredients. The IV has not been determined by anyone - the variables simply exist, such as being old or young.
46
What are ethical issues
Theses arise when a conflict exists between the rights of participants in research studies and the goals of research to produce authentic, valid and worthwhile data
47
What is the BPS code of ethics
A quasi-legal document produced bu the British Psychology Society (BPS) that instructs psychologists in the UK about what behavior is and is not acceptable when dealing with participants. The code is built around four major principles: respect, competence, responsibility and integrity
48
What are the disadvantages of repeated groups/measures
- each participant has to do at least two tasks
- the order of theses tasks may be significant ORDER EFFECT
- can create BOREDOM which could deteriorate performance
- could IMPROVE performance
- demand characteristics
49
Advantages of repeated measures/groups
- the participant variables are controlled
- fewer participants needed
50
Disadvantages of independent measures/groups
- not the same participant variables
- confounding variables
- reduces validity
- uses random allocation
Individual differences between participants reduces internal validity
51
Advantages of independent measures/groups
- the order doesn’t effect the investigation
- avoids order effect
- less chance of demand characteristics
52
Advantages of matched pairs
- participants are only in one condition
- less chance of demand characteristics
- avoids order effect
- minimizes participant variables
53
Disadvantages of matched pairs
- participants can never be matched perfectly
- pre test may be required to help with matching
54
What are order effects
The effect that the order of an investigation is carried out
55
Strengths of lab experiments
- easy to control variables
- have a high internal validity
56
Limitations of lab experiments
- people know there in an experiment
- demand characteristics
- act unnaturally
- in a place there not familiar with
- might lack generalizability
- low external validity
57
Strength of field experiments
- people behave more naturally
- higher mundane realism
- produce more valid and authentic behavior
- high external validity
58
Limitations of field experiments
- lost control of some factors
- extraneous variables
- ethical issues
- cannot consent
- invasion of privacy
59
Strength of natural experiments
- natural behavior
- high external validity
60
Limitations of natural experiments
- take a long time
- hard to repeat
- might have other factors
- reduce generalizability
- less cause and effect
61
Strengths of quasi experiments
- controlled conditions
- share some strengths with lab experiments
62
Limitations of quasi experiments
- confounding variables
- they cannot claim the IV has caused any observed change
63
Description of random sampling
- all members of the target population have an equal chance to be selected
- obtain a complete list of all the members in the target population
- all names are assigned a number
- using a lottery method the sample group is selected
64
Strengths of random sampling
- potentially unbiased
- extraneous variables should be equally divided between the different groups
- increasing internal validity
65
Limitations of random sampling
- can be biased
- all of one group may be picked when there are others in the target population (age, gender…)
- some groups might not be represented
- the sample might not represent the target population fairly
66
Description of opportunity sampling
Researcher asks whoever is around at the time of their study if they are willing and available to take part in their investigation
67
Strengths of opportunity sampling
- convenient
- method is much less costly as you do not need a list of members
- this allows for researchers to complete investigations quicker
68
Limitations of opportunity sampling
Two forms of bias
- the sample is unrepresentative of the target population
- specific area meaning it cannot be generalized
- the researcher has complete control over who they pick which could lead to researcher bias
69
Description of volunteer sampling
- involves participants selecting themselves to be a part of the investigation
- the researcher may place an advert in the newspaper or willing participants may raise there hand when asked
70
Advantaged of volunteer sampling
- easy
- it requires minimal input allowing it to be completed faster
- the researcher ends up with participants who are more engaged
71
Limitations of volunteer sampling
- volunteer bias
- asking for volunteers may attract certain people
- this can lead to the results not being generalized
72
Description of systematic sampling
- every nth member of the target population is selected
- n = size of target population / sample size
- a sampling frame and sampling system is used
- they then work through the list to get their sample groups
73
Strengths of systematic sampling
- objective
- once the selection system has been established the researcher has no influence over who is chosen
- allows for no bias
74
Limitations of systematic sampling
- this method takes a long time
- participants may refuse to take part, resulting in volunteer sampling
- same limitations as random sampling
75
Description of stratified sampling
- the researcher identifies the different strata making up the population
- the proportions are then worked out
- the participants from each stratum as then found using random sapling
76
What is a strata
A sub groups of the population
- age
- gender
- hair colour
77
Strengths of stratified sampling
- produces a representative sample because it is designed to accurately reflect the composition of the population
- this allows the results to be generalized
78
Limitations of stratified sampling
- if the researcher doesn’t know the stratas they can’t use this sampling
- the identified strata cannot reflect all the ways that people are different
- complete representation of the target population is not possible
79
What is validity
How accurate something is
- accuracy
80
What is internal validity
Whether or not the extraneous variables are causing the change in the dependent variable
- yes = low internal validity
- no = high internal validity
81
What is external validity
How well the results of the study can be generalized outside the study itself
82
What is ecological validity
Do the findings really represent other situational places and condition
83
What is mundane realism
Is the task like a real life task
84
What are some of the 1990 BPS ethical guidelines
- informed consent
- deception
- right to withdraw
- protection from harm
- privacy
- confidentiality
- debriefing
85
What are ethics
Conforming to accepted professional standards of conduct
- what you can and cannot do
86
What is informed consent
- participants have been told the aims of the investigation before hand
- allows them to make informed choices
- told their rights (RTW…)
- parental consent (-16)
- no payment can be made if it can induce risk taking behavior
- safeguarding
87
What are demand characteristics
- when participants might change their behavior after being told what they are doing
88
What is retrospective consent
Asking the participants if they can use their results after the investigation has happened
89
What is presumptuous consent
As a group of people simular to the ones you want to study and use their answers to presume
90
What is prior-general consent
Giving the participants a list of studies that they might do and get them to pick the ones they are happy to do
91
What is right to withdraw
- participants need to know they can withdraw at any time
- still must be payed in full
- may be done retrospectively by refusing permission for their data to be used
- must use language that participants are able to understand (young children, second language)
92
What are the different types of consent
- informed consent
- retrospective consent
- presumptuous consent
- prior-general consent
93
What is consent
When participants are allowing for something to happen
94
What is deception
Deliberately misleading or withholding information from participants
- allowed but should be avoided
- must have strong medical or scientific justification
- have to talk to a disinterested colleague or ethics committee before doing anything involving deception
95
Solutions for using deception
- use prior-general consent (must contain a deception investigation)
- use presumptuous consent
- give participants the right to withdraw
96
What is protection from harm of participants
- should be protected from physical or mental harm
- no more then they would experience in daily life
- participants should be asked about health factors/risks
- must be able to contact investigators at a later date
97
What is confidentiality
Our rights written in law under the Data Protection Act
98
What is privacy
Participants have the right to control information about themselves
99
Confidentiality in investigations
- when you collect data is has to remain private
- anonymity
- use initials
- lock results away
- legislations should be adhered to
- if confidentiality cannot be guaranteed participants should be made aware
100
Privacy in investigations
- can only carry out observations in public places unless you have been given permission before
- results have to be confidential: invasion of privacy
101
What is debriefing
- tell participants the real purpose of you investigation
- participants leave in the same state that they arrived
- must allow participants to ask questions
102
Giving advice and colleagues in investigations
- your duty to inform participants if they need help
- do not give advice if not your field
- must provide counseling if required afterwards
- watch other psychologists
- if they break codes
- tell them what they might need to do
- encourage them to rethink
103
What is an incentive to take part
Something that a participant is given to make them do the investigation
- participants shouldn’t be bribed or promised rewards
- money
104
What is a pilot study
A small scale version of an investigation that takes place before the real investigation
105
What is the aim of a pilot study
Allows the researchers to make changes or modifications if necessary
106
What type of studies can pilot studies be used for
All type of experimental methods
- experiments
- questionnaires
- interviews
107
What is a single blind procedure
Participants aren’t told the aim of the investigation
- what condition they are in
- if there are other conditions
108
What is the advantage of single bind procedures
Any information that might create expectations is not revealed until the end of the investigation
- participant bias
109
what is the disadvantage of single blind procedures
The researcher knows what is happening
- demand characteristics
110
What is a double blind procedure
Neither the participants nor the researcher is aware of the aims of the investigation
111
What is the control group
The baseline group
112
What is the purpose of having a control group
Allows for comparison
113
What does a large difference between the experimental group and control group show
The cause of the effect was the independent variable
114
What are the different type of observation
- naturalistic
- controlled
- covert
- overt
- participant
- non-participant
115
What is naturalistic observation
Watching and recording behaviour in the setting within which it would normally occur
116
What is controlled observation
Watching and recording behaviour within a structured environment
- some variables are managed
117
What is covert observation
Participants behaviour is watching and recorded without their knowledge and consent
118
What is overt observation
Participants behaviour is watched and recorded with their knowledge and consent
119
What is participant observation
The researcher becomes a member of the group whose behaviour their watching and recording
120
What is non-participant observation
The researcher remains outside of the group whose behaviour they are watching and recording
121
What are the limitations of observations
- observer bias. They can interpret the information they are given
- cannot demonstrate causal relationships. Can be used to detect cause and effect relationships
122
Strengths of naturalistic observation
- high external validity
- findings can be generalised
123
Weaknesses of naturalistic observation
- hard to replicate: lack of control
- hard to find patterns: confounding/extraneous variables
124
Strengths of controlled observation
- less chance of confounding and extraneous variables
- replication of observations is easier
125
Weaknesses of controlled observation
- produces findings that might not easily be applied to everyday life
126
Strengths of covert observation
- removes chance of demand characteristics
- increased internal validity
127
What are the weaknesses of covert observation
- questionable ethics
128
Strengths of overt observation
- more ethically acceptable
129
Weaknesses of overt observation
- demand characteristics
- participants may change their behaviour
130
Strengths of participant observation
- increased inside into the lives of the participants
- increased external validity
131
Weaknesses of participant observation
Researcher may lose objectivity
- may have created relationships
- may change their findings
132
Strengths of non-participant observation
- maintains objective data
- less chance of them adopting a local lifestyle
133
Weaknesses of non-participant observation
- may lose insight into the participants lifestyle
134
What is a behavioural category
When a target behaviour is broken up into components that are observable and measurable
- operationalised
135
What is event sampling
A target behaviour or event is first established then the researcher records this event every time it occurs
136
What is time sampling
A target individual or group is first established then the researcher records their behaviour in a fixed time frame
- every 60 seconds
137
What is unstructured observation
- writing down everything you see
- rich in detail
138
When is unstructured observation appropriate
When observations are small in scale and involve few participants
139
What is an example of unstructured observation
Observing the interaction between a couple and a therapist in a relationship counselling session
140
What is structured observation
- when there is too much going on for the researcher to record it all
- simplifies the behaviours into behavioural catagories
141
Strengths of time sampling
- reduces the number of observations that have to be made
- gives the researcher more time to record the behaviour
142
What type of data is produced with structured observation
Quantitative data
143
What type of data is produced with unstructured observation
Qualitative data
144
Strengths of unstructured observation
- rich and depth in detail
145
What do behavioural categories have to be
Non require further interpretation
- observerable
- measurable
- self evident
146
What is observer bias
When the researchers expectations, opinions or prejudices influence what they observe or record
- happens when the observer is aware of the aim of the investigation
147
How can you minimize observer bias
- double blind techniques
- use multiple observers
- standardised procedure
148
What is Inter observer reliability
The extent to which there is agreement between two or more observers involved in observations of a behaviour
- measured by correlating the observations
- checks for consistency
149
How do you do Inter observer reliability
- both observers watch the same people using the same checklist
- correlate the number of observations for the observers for each category
- 80% agreement = reliable
150
What is the general rule for inter observer realisability
(Total number of agreements) / ( total number of disagreements) > 80%
151
What are self-report techniques
Any method where a person is asked to state or explain their own feelings, opinions, behaviours or experiences related to a topic
152
What is a questionnaire
A set of written questions used to assess a persons thoughts or experiences
153
Strengths of questionnaires
- cost effective
- dont need the researcher present
- data is usefully straight forward to analyse
- statistical analyses and comparisons
154
Weaknesses of questionnaires
- demand characteristics
- social desirability
- response bias ( same end of a rating scale)
- acquiescence bias (regardless of context always choose yes)
155
What is a closed question
- fixed number of responses
156
Example of closed questions
- two options ( yes, no)
- scale from 1 - 10
157
What are open questions
Does not have a fixed range of answers
- produces lots of detail
158
Pros of open questions
- produce qualitative data
- wide range of different responses
159
Cons of open questions
- answers can be difficult to analyse
160
Pros of closed questions
- easy to analyse
- data can be turned in quantitative data
161
Cons of closed questions
- may lack depth and detail
162
What are likely scale questions
Responses indicate their agreement with a statement using a scale of usually 5 points
163
What are rating scale questions
Participants identify a value that represents their strength of feeling about a particular topic
164
What are fixed choice option questions
- includes a list of possible options
- participants indicate those that apply to them
165
What are features of good questions
- no overuse of jargon
- be neutral
- avoid double barrelled question
- avoid double negatives
- CLARITY
166
What is jargon
Technical terms
167
What is an interview
A live encounter where one person asks a set of questions to assess an interviewee’s thoughts or experiences
- pre set questions
- thought up as you go
168
What are structured interviews
Made up of pre determined questions
169
What are un-structured interviews
No set question
- interactions are free flowing
170
What are semi-structured interviews
Contain both a list of questions and follow up questions
171
Strengths of structured interviews
Easy to replicate because of standardised format
- reduced differences between interviewers
- less interviewer bias
172
Weaknesses of structured interviews
Limited richness of data collected
- further questions cannot be asked
173
Strengths of unstructured interviews
More flexibility
- researcher can change the questions
- allows participant to talk about what they want
174
Weaknesses of unstructured interviews
Interviewer bias
- drawing firm conclusions can be difficult to make
175
What is interviewer bias
When the interviewers beliefs of opinions affect the questions they ask
- can happen consciously or unconsciously
176
Which type of interview does interviewer bias usually occur in
Unstructured interviews
177
Ways to prevent interviewer bias
- use structured interviews
- standardised script and list of instructions
178
What is correlation
A statistical technique measuring the relationship between two or more co-variables
- looks at the relationship not cause and effect
179
What is a co-variable
The variable investigated within a correlation
180
What is the difference between correlations and experiments
- no manipulation (two DV’s)
- no cause and effect
181
What is a positive correlation
Positive relationship between two variables
- +ve gradient
182
What is a negative correlation
Negative relationship between two variables
- -ve gradient
183
What is no correlation
No relationship between two variables
184
What are intervening variables
Know as the ‘third variable problem’/‘mediator variable’
- factors playing a role between 2 other co-variables
- cannot be observed
185
Strengths of correlations
- can be used as a starting point for research
- preliminary tool for research
- precise measure of how two variables are related
- quick and economical to carry out
- no controlled environment
- can use secondary data
186
Weaknesses of correlations
Correlations dont prove cause and effect
- lack of experimental manipulation
- interviewer bias
187
What are the different types of data
- qualitative
- quantitative
- primary
- secondary
- meta-analysis
188
What is qualitative data
Expressed in words rather than numbers or statistics
- written description of thoughts, feelings and opinions
189
Examples of qualitative data
- unstructured observations
- counselling
- interview
- diary entry
190
What is quantitative data
Expressed numerically
191
How is quantitative data represented
- graphs
- charts
- …
192
What is primary data
Data collected by the researcher for the purpose of the investigation
193
What is secondary data
Data that has been collected by someone else
- data that already exists
194
Examples of secondary data
- journal articles
- books
- websites
195
Strengths of qualitative data
- more richness in data
- gives pps chance to fully report their feelings, thoughts or opinions
- external validity
196
Weaknesses of qualitative data
- difficult to analyse
- hard to summarise statistically
- conclusions can rely of subjective interpretations
197
Strengths of quantitative data
- easy to analyse
- conclusions are made from objective interpretations
198
Weaknesses of quantitative data
- lack of richness of data
- dont allow pps to fully say what they want to
- low external validity
199
Strengths of primary data
- authentic data for the investigation taking place
- questionnaire/interview can be designed for the pps
200
Weaknesses of primary data
- requires time and effort
201
Strengths of secondary data
- inexpensive
- desired information may already exist
202
Weaknesses of secondary data
- substantial variation in the quality and accuracy of secondary data
- challenges the validity
203
What is meta-analysis
A form of research method that uses secondary data
- pools together similar data and draws a conclusion from it
204
Strengths of meta-analysis
- larger, more varied sample
- results can be generalised across larger populations
- increased validity
205
Weaknesses of meta-analysis
- publication bias
- might not select all relevant studies
- conclusions only represent some of the relevant data
206
What are the measures of central tendency
- mean
- median
- mode
207
What are descriptive statistics
The use of graphs, tables and summary statistics to identify trends and analyse sets of data
208
Examples of descriptive statistics
- mean
- median
- mode
209
What are measures of dispersion
- range
- standard deviation
210
What does standard deviation tell you
How far the score deviate from the mean
211
What does a large standard deviation mean
Not all pps were effected by the IV in the same way
212
What does a low standard deviation tell us
The data is tightly clustered around the mean
- pps respond in a similar way
213
Limitations for both mean and standard deviation
Can be distorted by a single extreme value
214
What are the different ways to present quantitative data
- line graph
- scattergraph
- histogram
- bar chart
215
When are bar charts used
- data is in categories
- discrete data
- bars are separated
216
When are histograms used
- bars touch
- data is continuous
- shows the frequency on y-axis
217
What is a scatter gram used for
- correlations
- show associations between co-variables
218
What is normal distribution
A bell-shape curve showing where pps fall in an investigation
- symmetrical
219
Where is the mean, median and mode in normal distribution
All in the center
220
What is skewed distribution
When the distribution appears to lean to one side or the other
221
Which direction is a positive skew of distribution
Towards the left
- mode highest part
- mean lowest part
222
Which direction does a negative skew of distribution go
Towards the right
- mode highest part
- mean lowest part
223
What is a peer review
The assessments of scientific work by others who are specialists in the same field
- ensure that any research intended for publication is of high quality
224
What are the main aims of peer review
- to allocate research funds
- to validate the quality and relevance of research
- to suggest amendments of improvements
225
Why is anonymity a problem in peer reviews
- experts remain anonymous
- can use this to criticise rival researchers
- as competing for research funds
226
Why is publication bias a problem in peer review
- only want to publish significant findings
- prefer to publish positive findings
- creates a false impression of the current state of psychology
227
Why is burying groundbreaking research a problem in peer review
- wish to maintain the status quo within specific scientific fields
- especially critical of research that contradicts their own view
- established scientists more likely to be chosen
- slowing down the rate of change in particular fields
228
Weaknesses of peer review
- anonymity
- publication bias
- burying groundbreaking research
229
What are case studies
An in depth investigation, description and analysis of a single individual, group, institution or event
230
What is content analysis
A research technique that enables the indirect study of behaviour by examining communications that people produce
- in texts, emails, TV, film and other media
231
What is coding
The initial stage of content analysis
- the content is split into different categories
- words, sentences, phrases
232
What is thematic analysis
Type of content analysis
- results are qualitative
- general themes are used
233
Strengths of case studies
- offer rich, detailed insights of unusual forms of behaviour
- help contribute to our insight typical functioning
- can generate hypotheses for future studies
234
Weaknesses of case studies
- harder to generalise findings
- subjective interpretations
- evidence can lack validity
235
Strengths of content analysis
- can circumnavigate many ethical issues as already in public domain
- high external validity
- can produce both qualitative and quantitative data
236
Weaknesses of content analysis
- people are studies indirectly
- data is analysed outside of its original context
- can lack objectivity
237
What is reliability
A measure of consistency
238
Ways to assess/test reliability
- test retest
- Inter observer reliability
- measuring reliability
239
What is the test-retest
- giving the same test to the same people on different occasions
- if reliable results should be the same or very similar
- must be sufficient time between each test
240
How can you improve reliability in questionaries
- remove complex or ambiguous question as they can be interpreted differently
- replace open questions with closes, fixed-choice questions
241
How to improve reliability in interviews
- use the same interviewer each time
- pre set questions
- structured interview
242
How to improve reliability in observations
- behavioural categories are operationalised
243
How to improve reliability in experiments
- use standardised procedures
244
What is validity
The extent to which an observed effect is genuine
- does it measure what it is supposed to measure
- can it be generalised
245
What are the different types of validity
- internal
- external
- temporal
- face
- concurrent
- ecological
246
What is internal validity
Whether the effects observed in an experiment are du to the manipulation of the IV and not other factors
247
What is external validity
Relates to factos outside of the investigation
- can it be generalised to other settings
- other populations
- other people
- other times
248
What is ecological validity
The extent to which findings from a research study can be generalised to other settings and situations
- type of external validity
249
What is temporal validity
The extent to which findings from a research study can be generalised to other historical times and eras
- type of external validity
250
What is face validity
A basic form of validity in which a measure is scrutinised to determine whether is appears to measure what it is supposed to measure
251
What is concurrent validity
The extent to which a psychological measure relates to an existing similar measure
- does a test match up to a pre existing one
252
How to improve validity in experiments
- control groups
- standardised procedures
- single/double-blind procedures
253
How to improve validity in questionaries
- use of a lie scale
- anonymity
254
Ways to improve validity in qualitative research
- use differnt sources
- interpretive validity
255
What are the different types of statistical tests for repeated measures/ matched pairs
- sign test
- Wilcoxon
- related t test
256
What are the different statistical tests for independant groups
- chi square
- Mann-Whitney
- unrelated t test
257
What are the statistical tests for correlations
- chi-square
- spearman’s rho
- pearson’s moment
258
What are the three things you use to choose a statistical test
- test of difference or significance
- experimental design
- level of measurement
259
What does a statistical test determine
Which hypothesis is true
- which you accept
- which you decline
260
What is the normal level of significance used
0.05/5%
261
How is level of significance written
P<=0.05
262
What does a significant level of 0.05 mean
There is up to 5% chance that the results were due to chance
263
What is the critical value in stat testing
The value that is used to compare the calculated value with
264
What is the calculated value
The value you work out
265
What is the critical value in a sign test
The number of least occurring signs
- positive or negative
- equal are ignored
266
What things are needed to know what table of critical values to use
- one or two-tailed test
- number of participants/degrees of freedom
- level of significane
267
When is a level of significance of 0.01 or 1% used
- human cost
- drug trials
268
What is a type 1 error
Rejecting a true null hypothesis
- false positive
269
What is a type 2 error
Accepting a false null hypothesis
- false negative
270
What level of significance causes type 1 errors
- lenient levels
- 0.1/10%
271
What level of significance causes type 2 errors
- strict levels
- 0.01/1%
272
What are the different parts of a scientific report
- abstract
- introduction
- method
- results
- discussion
- references
(- appendix)
273
What is in the abstract
The key details of the research report in a brief summary
- aims and hypotheses
- method/procedure
- results
- conclusion
274
What is in the introduction of a scientific report
Literature review
- past research on similar topics
- aim and hypothesis of current investigation
275
What is in the method of a scientific report
Description of what the researchers did to allow for replicability
- design
- sample method/size
- materials/apparatus
- procedure: briefing, standardised instructions, debriefing
- ethics
276
What is in the results of a scientific report
Summarises the key findings
- descriptive statistics (tables, graphs, charts)
- inferential statistics (statistical test, calculated/critical value, level of significance)
- raw data
- qualitative methids
277
What is in the discussion of a scientific report
Summary of the results
- verbal form
- explanation in terms of psychological theories
278
What is the referencing of a scientific report
List of sources referred to or quoted in the article
- Harvard referencing
279
What are the features of science
- paradigms and paradigm shifts
- theory construction and hypothesis testing
- falsifiability
- replicability
- objectivity and empirical method
280
What is an empirical method
Approached that are based on gathering evidence through direct observation and experience
281
What is a paradigm
Set of shared assumptions and agreed methods which in a scientific disipline
282
What is a paradigm shift
- results of a scientific revolution
- significant change in the dominant theory within a scientific disipline
283
What is falsifiability
- a science must be falsifiable
- possibility of something being proved wrong
284
What is theory construction
- developing an explanation for something
- systematically gathering evidence
- organising into coherent theories
285
What are the two different types of theory construction
286
What is a parametric test
All tests done with interval data
287
What are non-parametric tests
All tests done with nominal or ordinal data
288
What is the formula when writing the results of a statistical test
- if you accept the null/experimental hypothesis
For a … tailed test, when p<… and N = … , the CV is …
To be significant the OV must be …
OV is … than CV. So there is (more or less than …%) probability the results were due to chance so
Accept (null/experimental) hypothesis. Reject (null/experimental) hypothesis
289
What is the hypothetico-deductive model
Questions -> hypothesis -> test -> theory -> questions …
Cycle repeats over and over again
290
What are the two different models of the scientific process
- inductive
- deductive
291
What is the inductive model of the scientific process
- goes from particular to general
- aims to develop a theory
- Issac Newton: law of gravity
- only explains existing data (what you already think is true)
292
What is the deductive model of the scientific process
- from general to particular
- starts with theory then tests it
- Darwin: theory of evolution
293
What is the order of steps for the inductive model of the scientific process
- observation
- observe a pattern
- theory/general conclusion
294
What is the order of steps for the deductive model of the scientific process
- existing theory
- falsifiable hypothesis
- test the hypothesis
- analyse and test the data
- accept or reject null hypothesis
295
What is ordinal data
Ranking
- scores on a rating scale
- scores on a test if not of equal difficulty
296
What is nominal data
Most basic level
- categories
297
What is interval data
Exact measurements
- objective units
