Definitions Flashcards

(243 cards)

1
Q

Respect:

Informed consent

A

Participants are told the nature and purpose of the study (without revealing too much thus creating demand characteristics) so they have full knowledge and can consent to the study

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2
Q

Respect:

Right to withdraw

A

Participants must be aware that they don’t have to take part in the study and can withdraw at any time with no repercussions

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3
Q

Respect:

Confidentiality

A

A participants personal information will be kept secure and protected through out the study and will be destroyed after the study.

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4
Q

What three subsections are under the heading respect?

A

Informed consent, right to withdraw and confidentiality

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5
Q

`Competence

A

The experimenter must know what their limits are and not go past these, also the participant must know what their examiner is capable of with no lies.

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6
Q

Responsibility:

Protection of participants

A

Participants should not experience unnecessary harm or have a negative psychical or mental effects unless it has been agreed with in the informed consent

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7
Q

Responsibility:

Debreif

A

Participants should experience a post study interview where they are told the nature of the experiment, what information they didn’t already know and they have the opportunity to ask any questions

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8
Q

What two subsections are under the heading responsibility?

A

Protection of participants and debreif

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9
Q

Integrity:

Deception

A

When we don’t tell the participants the true aim of the excrement or lie to them about what is happening during the study

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10
Q

What does the experiment research method establish?

A

Casual relationships between variables.

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11
Q

Definition of variiables

A

Thin gs that can be changed or manipulated

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12
Q

Independent variable - IV

A

Variables we deliberately alter (cause)

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13
Q

Dependent variables - DV

A

Variables we measure (effect)

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14
Q

Extraneous variables

A

Any variable other than the IV that could potentially affect the DV and confound the results. We control the effect of those to establish cause and effect relationships

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15
Q

Participant variables

A

Factors within a person that can vary over time or with a situation - boredom. Also factors that differ between people - age, sex, race

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16
Q

Situation variables

A

Factors that can vary in an environment - noise, temperature

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17
Q

Alternative/experimental hypothesis - HI

A

There will be a significant different, the IV will have an effect on the DV

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18
Q

Give an example of an alternative/experimental hypothesis

A

There will be A significant difference in the throwing accuracy between participants that throw a ball at a target with a silent audience and participants that throw a ball at a target with a noisy audience

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19
Q

Null hypothesis - H0

A

There will be NO significant difference - The IV wont have an effect on the DV

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20
Q

Give an example of a null hypothesis

A

There will be NO significant difference in the throwing accuracy between participants that throw a ball at a target with a silent audience and participants that throw a ball at a target with a noisy audience

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21
Q

Falsification hypothesis

A

A operationalised hypothesis that can be proven false

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22
Q

One tailed hypothesis

A

A hypothesis that predicts a direction for the difference

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23
Q

Give an example of a one tailed hypothesis

A

Girls will remember more words than boys - there’s a direction for the difference and we know which way

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24
Q

Two tailed hypothesis

A

A hypothesis that doest predict the direction of the difference

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25
Give an example of a two tailed hypothesis
There will be a difference between the number of words that girls and the number of words boys will remember
26
Repeated measures design
The same participants are used in each condition, so each participant is their own control
27
Give an advantage of repeated measures design
Fewer people are needed for the experiment as the participants used in one experiment are also used in the other
28
Give a disadvantage of repeated measures design
Participants can experience order effects - tiredness, boredom ect as they're used in both expierements
29
Independent measures design
Different participants are assigned to each condition, so participants only experience one condition
30
Give one an advantage to independent measures design
Participants are less likely to experience order effects as they only experience one condition
31
Give one disadvantage to independent measures design
More participants are needed as different participants are used in each condition
32
Matched pairs design
Participants are paired with another participant in the other condition with similar important participant variables in the study
33
Give an advantage of matched pairs design
Participants are less likely to experience order effects as they're only used in one condition
34
Give a disadvantage of matched pairs design
It's time consuming as you have match participants with similar important characteristics which can be a hard process
35
Participant variables
The differing characteristics between participants, age, background ect
36
Order effects
Effects caused by repeating something, tiredness, boredom ect
37
Give an example of a participant variable
Age
38
Give an example of an order effect
Tiredness
39
Counterbalanceing
Varying the order that participants experience conditions, used to balance out order effects.
40
Demand characteristics
Clues about the experiment or situation that help participants guess the aim/how their supposed to act so they act in this way
41
Target population
The group of people the research is interested in describing. We draw out sample from this group and aim to generalise our findings to this group
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Sampling
The selected participants, taken from the target population, that we use in our reasearch
43
Sampling method
The technique used to choose our sample from the target population
44
Generalisability
The extent to which our results can be applied to our target population
45
Random sampling
All participants in the target population have an equal chance of being picked
46
Give an advantage of random sampling
It's the most likely method to gain a representative sample
47
Give a disadvantage of random sampling
It's time consuming to get all the target audience's names
48
Opportunity sampling
Participants that are most easily available at the time
49
Give an advantage of opportunity sampling
The easiest method as it is time efficient and cost effective to locate the participants as it's who is available at that time
50
Give a disadvantage of opportunity sampling
Likely to produce biased/un-representative sample, Participants will probably have similar characteristics so we will be unable to generalise our results to the target population
51
Representativeness
The extent to which our sample reflects the characteristics of our target population
52
Self-selected sampling
Participants have selected themselves
53
Give an advantage to self-selected sampling
It reduces participant attrition as the participants have chosen to take part
54
Participant attrition
Participant drop out rate
55
Give a disadvantage of self selected sampling
Participants are likely to have similar characteristics as they've seen the add in the same place and chosen to take part meaning they have similar participant characteristics. This means the sample is more biased and not a representative sample
56
Snowball sampling
Initial participants are used to generate other participants (word of mouth)
57
Give an advantage of snowball sampling
Can help researchers identify participants that are difficult to locate - gamblers and drug addicts
58
Give a disadvantage of snowball sampling`
The sample is more likely to be biased, making it difficult to generalise our results to the target population
59
Ecological validity - EV
The extent to which we can generalise our results to everyday/real life settings or situations
60
Laboratory experiments
The IV is manipulated in a controlled environment
61
Give an advantage of laboratory experiments
High control over extraneous variables making it easier to establish cause and effect relationships
62
Give a disadvantage or laboratory expierements
The environment may be artificial meaning the experiment has low ecological validity
63
Field experiments
The IV is manipulated in a natural/everyday setting
64
Give one advantage of field expierements
The environment is natural and less artificial meaning it has high ecological validity
65
Give one disadvantage of field experiments
Participants aren't usually aware that we're studying them so we break ethical guidlines
66
Quasi expierements
Experimenter doesn't manipulate the IV and it is often naturally occurring
67
Give an advantage of quasi expieremnts
Allows us to research an IV that we can't ethically manipulate
68
Give a disadvantage of quasi expierements
We cant limit the amount of control over the extraneous variables
69
Control standardisation
Cause and effect relationships are established when extraneous variables are controlled, this adds validity to our method and findings. Also controls the experience of every participant meaning its easier to replicate
70
Cause and effect relationships
If we've collected data empirically, we can show that to any significant level. One variable caused and effect on another. The more this effect is replicated the more confident we can be in the reliability of this finding
71
Inductive reasoning
Makes broad generalisations from specific observations, make observations, look for a pattern, make a generalisation and infer an explanation/theory. We work from specifics to general theories meaning there is more room for errors.
72
Deductive reasoning
A form of valid reasoning. You start with a general statement/theory, examine all the consequences of the theory/statement then research all logic as its the truth. General to the specific
73
Give an example of inductive reasoning
Carol is a teacher, Carol is a Geordie, all teachers are Georide
74
Give an example of deductive reasoning
All woman will die, Carol is a woman, Carol will die
75
Falsification
An important characteristic of science is that we produce theories and hypotheses that can be proven false. A theory that can't be proven proven false can't advance our understanding of the world or be judged as a better/worse explanation than another theory
76
Objectivity
Being uninfluenced by personal opinion, past experiences or bias.
77
Fact
Statements that we know to be true through direct observation
78
Observation
Can be made directly or through using tools - temperature, thermometer
79
Hypothesis
Precise testable predictions that can be falsified (proven false)
80
Theories
Explanation based on evidence and collected using scientific methods
81
Empirical evidence`
Data collected through direct observation or experimentation without evidence
82
Quantitative measures
Quantitative data is observable and objective, it should not rely on opinions, beliefs or unobservable data therefore its objective, empirical and has greater validity
83
Describe the steps in the hypothetico-deductive model
Ask a question - Do background research - Construct a hypothesis - Test with an experiment - Procedure working? (no - trouble shoot, check all steps and set up then return to test with an experiment) yes - Analyse data and draw conclusions - (reject null hypothesis - communicate results) or (reject alternative hypothesis then communicate results or create a new hypothesis and try again)
84
Observation method
Systematically watching and taking direct records or participants verbal and physical behaviour
85
Give an advantage of observation methods
We are able to see what participants do rather than what they say they do
86
Give a disadvantage of observation methods
We don't know why they are doing what they are - We need a self report to know this. We may see what we expect to see, not what is actually there.
87
Covert observations
Observing a participants without their knowledge
88
Give an advantage of covert observations
Participants are more likely to behave naturally as they don't know their being watched
89
Give a disadvantage of covert observations
Observing participants without their knowledge breaks societies codes of ethics and conduct - consent, deception, right to withdraw and privacy (unless it's in a public place)
90
Overt observations
A participants is aware that we are observing their behaviour
91
Give an advantage of overt observations
It's ethical as it avoids breaking any ethical guidlines
92
Give a disadvantage of overt observations
It's likely to introduce demand characteristics causing participants to alter their behaviour
93
Participant observations
Observer participates in the behaviour being observed
94
Give an advantage of participant observations
Likely to produce unique insights into rare behaviour as we are insifers
95
Give a disadvantage to participant observations
We can become objective as an observer because we have 'made friends' with the participants
96
Non-participant observations
The observer is not a participant in the behaviour being observed
97
Give an advantage of non-participant observation
We remain objective as we aren't taking part in the behaviour
98
Give a disadvantage of non-participant observation
We may misinterpret what we are seeing as we aren't part of the behaviour being observed so we wont fully understand
99
Structured observation
Recording behaviour in a systematic manner to organise out data
100
Give an example of structured observation
A coding scheme
101
Give an advantage of a structured observation
Results are likely to be quanitative so are easier to analyse
102
Give a disadvantage of a structured observation
Behaviours not on our coding scheme are likely to be missed
103
Unstructured observation
Observing all behaviour that might be relevant without any system
104
Give an advantage of unstructured observation
Useful when we are studing behaviour that is unpredictable
105
Give a disadvantage of unstructured observation
The behaviours that most catch our attention might not be the most important/revelent to record
106
Naturalistic observation
Observing participants in a natural setting that would be the same if the observer wasn't present
107
Give an advantage of naturalistic observation
Most likely to see natural behaviour and fewer demand characteristics meaning our observations have a higher EV
108
Give a disadvantage of naturalistic observation
Often done covertly so it has ethical issues
109
Controlled observation
The environment is changed or controlled because of the observation. Often used because there is an IV - experiment using an observation )
110
Give an advantage of a controlled observation
Greater control of the environment so fewer extraneous variables
111
Give a disadvantage of controlled observation
Greater control means the experiment will be artificial so the behaviour is less natural
112
Coding frames
A list of behavioural categories e.g tally chart
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Behavioural catogories
Dividing behaviour into categories in a structured observation. Good categories are precise and operationalised and will give us quantitative data
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Observer bias
When we lose our objectivity and see what we want to see/what we were expecting to see over what is actually there
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Observer effects
When the presence of an observer creates demand characteristics which influences a participants behaviour
116
Time sampling
Recording behaviour in a regular time interval - every 5 minutes
117
Give an advantage of time sampling
Its easier to conduct with a large group of people/with quickly changing behaviour
118
Give a disadvantage of time sampling
We cant record behaviour that occurs between intervals meaning rare behaviour is often missed
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Event sampling
Using behaviour categories and a coding frame and recording behaviour from our list each time it occurs during a specified time
120
Give an advantage of event sampling
Our results will be more representative of the usual behaviours that may not occur often
121
Give a disadvantage of event sampling
It can be difficult to conduct for a large group of participants or where behaviour is changing quickly meaning there's a greater chance we will miss an event
122
Self-report method
A method by which we ask participants about their own thoughts, feelings or opinions. Its the only method we can use to directly measure thoughts, feelings and opinions - questionnaires or interviews
123
Give an advantage of self-report method
They can give a valid measure of thoughts, feelings and opinions
124
Give a disadvantage of self report methods
Participants might lie, show social desirability or misunderstand out questions (all reduces validity)
125
Interviews
Usually conducted face to dace, they can be written down on the spot or tape recorded and transcribed
126
Give an advantage of interviews
Participants can ask questions if they don't understand
127
Give a disadvantage of interviews
Because they're conducted face to face participants can't be entirely anonomous, this could lead to greater evaluation anxiety and socially desriable answers
128
Social desirability
You give a socially desirability answer and not your true answer - you lie
129
Inter-rater reliability
the extent to which two or more raters in an observation/self report agree in the results they've collected
130
How can you improve inter-rater reliability
use operationalised categories Produce categories in a pilot study Train raters on how to use categories
131
Evaluation anxiety
Fear of being judged
132
Unstructured interview
There are no set questions but the interviewer may have a list of promps/topics and the questions follow on from the answers give.
133
Give an advantage of unstructured interviews
We can gather qualitative data so results may be richer and more in-depth
134
Give a disadvantage of unstructured interviews
Likely to cover a broad range of topics so it will be difficult to compare the results of different participants as they may be asked different things
135
Semi-structured interviews
Some questions are pre-determined but the interviewer has the freedom to follow up interesting responses
136
Give an advantage to semi-structured interviews
We can gather qualitative data so results may be richer and more in-depth
137
Give a disadvantage to semi-structured interviews
Likely to cover a broad range of topics so it will be difficult to compare the results of different participants as they may be asked different things
138
Structured interviews
Uses a predetermined set of questions asked in the same way for each participant
139
Give an advantage to structured interviews
They're easier to repeat with many participants as the questions don't change and their asked in the same way for each participant making them more reliable
140
Give a disadvantage to structured interviews
Its hard to follow up on interesting answers because the questions are restricted and you can't variate from them
141
Correlation method
A relationship between two variables. They don't look at whether one has affects the other. They use co-variables
142
Give an advantage of correlations
We can research variables that it would be unethical to research in an experiment
143
Give a disadvantage of correlations
We cant see cause and effect in a correlations, only a relationship between the two variables
144
Correlation coefficient
The relationship can be described in terms of its strength and direction, we use a mathematical measure of how related the two sets of data are.
145
What are the results in a correlation coefficient
+1 is a perfect positive correlation 0 is no correlation -1 is a perfect negative correlation
146
Reliability
The consistency of our measure, research, method, findings or data collected over time. CONSISTENCY IS KEY
147
Internal reliability
The extent to which a measure is consistent within it's self
148
Split half method of testing reliability
Test items are split and tested against each other e.g do the first half of the questions on a test match the second half?
149
External reliability
The extent to which a measure is consistent over time (is the interview in the beginning the same as the interview in the end?)
150
Test-retest reliability
Give participants a the same test on two different occasions and compare the results
151
Inter-rater reliability
Compare the results of two different observers/raters and check for consistency in the results
152
What are some factors that can affect reliability?
Level of control over extraneous variables - participant situational and experimental variables The extent to which our procedure is standardised Leading or poorly written questions on a questionnaire Poorley operationalised categories in an observation
153
Alternative hypothesis - HI
A hypothesis that predicts the significant relationship between two covariables
154
Give an example of an alternative hypothesis
There will be a significant correlation between the achievement in the AS psychology and attendance in the AS psychology course
155
Null hypothesis - H0
A hypothesis that predicts there will be no significant correlation between the two covariables
156
Give an example of a null hypothesis
There will be no significant correlation between the achievement in the AS psychology and attendance in the AS psychology course
157
One tailed (directional) correlation hypothesis
A hypothesis that predicts a significant correlation and specifies the direction
158
Give an example of a one tailed correlation hypothesis
There will be a significant POSITIVE correlation between attendance and grades in psychology
159
Two tailed (non-directional) correlation hypothesis
A hypothesis that predicts a significant correlation but doesn't specify the direction
160
Give an example of a two tailed correlation hypothesis
There will be a significant correlation between attendance and grades in psychology
161
Validation
The extent to which a study measures what it claims to measure
162
External validity
Can the findings be generalised beyond the original study
163
Internal validity
Does a study test what it claims to test?
164
Face (content) validity
Does the test appear to measure what it intends to measure? E.g - Hand size and IQ correlation is wrong
165
Construct
Does the test measure the 'construct' it intends to measure?
166
Concurrent validity
Does a new test give comparable results to an old established test?
167
Predictive validity
Do the test results accurately predict future behaviour?
168
Criterion validity
Do the test results accurately predict future behaviour?
169
Population validity
Can we generalise the results to populations beyond those tested in the study?
170
Ecological validity
Can we generalise the results to setting and situations beyond the setting of the study?
171
Mundame realism
How realistic/believable is a study compared to the everyday world
172
Demand characteristics`
Cues in a study procedure that indicate to a participant what is expected of them and can cause a participant to change their natural behaviour
173
Social desirable bias
Occurs when participants answer questions or present themselves in a more positive light - how society wants them to act
174
Researcher/observer effects
When the observer/researcher influences or effects a participants behaviour
175
Researcher/observer bias
When a researcher/observer expectations influences the results
176
Sampling methods
Some sampling methods are more likely to lead to samples with a higher/lower population validity
177
Experimental design
Some experimental designs lead to an increased chance of demand characteristics and/or order effects
178
Control of variables
Extraneous variables will influence whether we are testing the IV's isolated effect on the DV's
179
Less than
180
Much less than
181
It's reducable to
182
Less than or equal to
183
>
Greater than
184
>>
Significantly greater than
185
More than or equal to
186
Is not equal to, doesn't equal
187
~
Is similar to
188
Standard form
A way of writing down very large or very small numbers
189
Decimal form
A fraction written in a special form
190
Significant figures
Each of the digits of a of a number are used to express it, starting from the first non-zero number
191
Primary data
Data collected first hand - specific to your research
192
Secondary data
Data already collected - not specific to your research
193
Quantitative data
Numerical data that can be statistically analysed - answers to a closed question
194
Qualitative data
Rich, detailed, in-depth and descriptive data - responses to an open question
195
Nominal data
Individual categories under titles, collective scores under a heading
196
Give an example of nominal data
Age, gender
197
How do you display nominal data
Mode, bar chart or pie chart
198
Ordinal data
Ranking 1st, 2nd, 3rd not equal intervals
199
Give an example of ordinal data
Grades
200
How would you display ordinal data
Median, mode, bar chats, pie chars and frequency tables
201
Interval data
Continuous data where differences between intervals are equal - individual scores, set scored
202
Give an example of interval data
Temperature, time taken to complete work
203
How would you display interval data
Mode, median, mean, bar chart, pie chart, histograms and scatter graphs
204
Ratio data
Has an absolute zero and intervals are equal
205
Give an example or ratio data
Money, time
206
How would you display ratio data
Mode, median, mean, bar chart, pie chart, histogram and scatter graphs
207
Measures of central tendency
This is a single number that is calculated to describe the central position within a set of data, often it is not an actual value within your data set
208
Mode
Adding all your values together and dividing by the number of values
209
Give an advantages of mode
It includes every value within your data
210
Give a disadvantage of mode
Very sensitive to outliers, particularly with a small data set and it cant often be used for nominal data
211
Median
Median is the middle value
212
Give an advantage of median
It is less affected by extreme values and it can be used on interval and ordinal data
213
Give a disadvantage of median
Not as sensitive - doesn't take into account the exact values of each data and it cant be used for nominal data. It's meaningless for small data sets
214
Mode
Most frequent score
215
Give an advantage of mode
Can be used for any data set and is not affected by extreme scored/anomolies
216
Give a disadvantage of mode
Various values that meet the criteria it can be bi-modal | A mode may not be described where most data is concerned
217
Measures of dispersion
This value describes how spread out our data us
218
Variance
How spread out the data is around the mean
219
Range
The difference between the highest and lowest numbers. A large range means there's a lot of variability in the data
220
Standard deviation
The square root of the variance
221
Ratios
Shows the relation between two quantaties
222
Percentages
Representation of a rate or number out of 100
223
Fractions
A numerical quantity that is not a whole number - 1/4
224
Do a bar chart's bars touch or not?
They don't touch because they're not related
225
Do a histogram's bars touch or not?
Yes because its a continuous scale
226
Probability
The likely hood that something will happen between 0 and 1
227
Observed value
We calculate the probability that our results were due to chance using inferential statistics. Each test gets its own observed value, depending on the types of studies we have conducted and whether we expect our data to follow a normal distribution curve - parametric test - or if we believe our population won't be normal - non-parametric
228
Which test will follow a normal distributon curve
Parametric test
229
Statical significance
Statical significance is the probability that is high enough that we will reject our null hypothesis. We will work to a 0.05 significant level, this means that we can be 95% certain our IV is affected by our DV with a 5% likely hood our results were due to chance
230
Type 1 error
If our significance level is too generous we will increase the chances of a type one error. We reject a null hypothesis that is true
231
Type 2 error
If our significance label is too tight we increase the chances of a type two error. We accept a null hypothesis that isn't true
232
Peer review
The assessment of research by others who are experts in that filed (peers). usually done before publishing, essential check to prevent incorrect data from entering the public domain. Every researcher should be prepared to have their work scrutinised
233
What independent measures design do we use for nomianal data
Chi squad
234
What independent measures design do we use for ordinal data
Mann Whitney U
235
What independent measures design do we use for interval/ration data
Unrelated + test
236
What repeated measures design do we use for nomianal data
Binominal sign test
237
What repeated measures design do we use for ordinal data
Wilcoxon
238
What repeated measures design do we use for interval/ration data
Related + test
239
What test for correlation do we use for ordinal data
--------
240
What test for correlation do we use for nominal data
Spearmans rank
241
What test for correlation do we use for interval/ration data
Pearsons product moment
242
Define validity
Is there something getting in the way of measuring what they wanted to measure? Extraneous variables?
243
Define reliability
Is the study replicable? How consistent is the measuring device? Does the study have a standardised procedure?