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Psychology > Definitions > Flashcards

Definitions Flashcards

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
Q

Give an example of a two tailed hypothesis

A

There will be a difference between the number of words that girls and the number of words boys will remember

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26
Q

Repeated measures design

A

The same participants are used in each condition, so each participant is their own control

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27
Q

Give an advantage of repeated measures design

A

Fewer people are needed for the experiment as the participants used in one experiment are also used in the other

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28
Q

Give a disadvantage of repeated measures design

A

Participants can experience order effects - tiredness, boredom ect as they’re used in both expierements

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29
Q

Independent measures design

A

Different participants are assigned to each condition, so participants only experience one condition

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30
Q

Give one an advantage to independent measures design

A

Participants are less likely to experience order effects as they only experience one condition

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31
Q

Give one disadvantage to independent measures design

A

More participants are needed as different participants are used in each condition

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32
Q

Matched pairs design

A

Participants are paired with another participant in the other condition with similar important participant variables in the study

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33
Q

Give an advantage of matched pairs design

A

Participants are less likely to experience order effects as they’re only used in one condition

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34
Q

Give a disadvantage of matched pairs design

A

It’s time consuming as you have match participants with similar important characteristics which can be a hard process

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35
Q

Participant variables

A

The differing characteristics between participants, age, background ect

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36
Q

Order effects

A

Effects caused by repeating something, tiredness, boredom ect

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37
Q

Give an example of a participant variable

A

Age

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38
Q

Give an example of an order effect

A

Tiredness

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39
Q

Counterbalanceing

A

Varying the order that participants experience conditions, used to balance out order effects.

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40
Q

Demand characteristics

A

Clues about the experiment or situation that help participants guess the aim/how their supposed to act so they act in this way

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41
Q

Target population

A

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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42
Q

Sampling

A

The selected participants, taken from the target population, that we use in our reasearch

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43
Q

Sampling method

A

The technique used to choose our sample from the target population

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44
Q

Generalisability

A

The extent to which our results can be applied to our target population

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45
Q

Random sampling

A

All participants in the target population have an equal chance of being picked

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46
Q

Give an advantage of random sampling

A

It’s the most likely method to gain a representative sample

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47
Q

Give a disadvantage of random sampling

A

It’s time consuming to get all the target audience’s names

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48
Q

Opportunity sampling

A

Participants that are most easily available at the time

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49
Q

Give an advantage of opportunity sampling

A

The easiest method as it is time efficient and cost effective to locate the participants as it’s who is available at that time

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50
Q

Give a disadvantage of opportunity sampling

A

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

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51
Q

Representativeness

A

The extent to which our sample reflects the characteristics of our target population

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52
Q

Self-selected sampling

A

Participants have selected themselves

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53
Q

Give an advantage to self-selected sampling

A

It reduces participant attrition as the participants have chosen to take part

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54
Q

Participant attrition

A

Participant drop out rate

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55
Q

Give a disadvantage of self selected sampling

A

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

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56
Q

Snowball sampling

A

Initial participants are used to generate other participants (word of mouth)

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57
Q

Give an advantage of snowball sampling

A

Can help researchers identify participants that are difficult to locate - gamblers and drug addicts

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58
Q

Give a disadvantage of snowball sampling`

A

The sample is more likely to be biased, making it difficult to generalise our results to the target population

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59
Q

Ecological validity - EV

A

The extent to which we can generalise our results to everyday/real life settings or situations

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60
Q

Laboratory experiments

A

The IV is manipulated in a controlled environment

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61
Q

Give an advantage of laboratory experiments

A

High control over extraneous variables making it easier to establish cause and effect relationships

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62
Q

Give a disadvantage or laboratory expierements

A

The environment may be artificial meaning the experiment has low ecological validity

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63
Q

Field experiments

A

The IV is manipulated in a natural/everyday setting

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64
Q

Give one advantage of field expierements

A

The environment is natural and less artificial meaning it has high ecological validity

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65
Q

Give one disadvantage of field experiments

A

Participants aren’t usually aware that we’re studying them so we break ethical guidlines

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66
Q

Quasi expierements

A

Experimenter doesn’t manipulate the IV and it is often naturally occurring

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67
Q

Give an advantage of quasi expieremnts

A

Allows us to research an IV that we can’t ethically manipulate

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68
Q

Give a disadvantage of quasi expierements

A

We cant limit the amount of control over the extraneous variables

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69
Q

Control standardisation

A

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

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70
Q

Cause and effect relationships

A

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

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71
Q

Inductive reasoning

A

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.

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72
Q

Deductive reasoning

A

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

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73
Q

Give an example of inductive reasoning

A

Carol is a teacher, Carol is a Geordie, all teachers are Georide

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74
Q

Give an example of deductive reasoning

A

All woman will die, Carol is a woman, Carol will die

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75
Q

Falsification

A

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

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76
Q

Objectivity

A

Being uninfluenced by personal opinion, past experiences or bias.

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77
Q

Fact

A

Statements that we know to be true through direct observation

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78
Q

Observation

A

Can be made directly or through using tools - temperature, thermometer

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79
Q

Hypothesis

A

Precise testable predictions that can be falsified (proven false)

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80
Q

Theories

A

Explanation based on evidence and collected using scientific methods

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81
Q

Empirical evidence`

A

Data collected through direct observation or experimentation without evidence

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82
Q

Quantitative measures

A

Quantitative data is observable and objective, it should not rely on opinions, beliefs or unobservable data therefore its objective, empirical and has greater validity

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83
Q

Describe the steps in the hypothetico-deductive model

A

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)

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84
Q

Observation method

A

Systematically watching and taking direct records or participants verbal and physical behaviour

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85
Q

Give an advantage of observation methods

A

We are able to see what participants do rather than what they say they do

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86
Q

Give a disadvantage of observation methods

A

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.

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87
Q

Covert observations

A

Observing a participants without their knowledge

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88
Q

Give an advantage of covert observations

A

Participants are more likely to behave naturally as they don’t know their being watched

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89
Q

Give a disadvantage of covert observations

A

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)

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90
Q

Overt observations

A

A participants is aware that we are observing their behaviour

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91
Q

Give an advantage of overt observations

A

It’s ethical as it avoids breaking any ethical guidlines

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92
Q

Give a disadvantage of overt observations

A

It’s likely to introduce demand characteristics causing participants to alter their behaviour

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93
Q

Participant observations

A

Observer participates in the behaviour being observed

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94
Q

Give an advantage of participant observations

A

Likely to produce unique insights into rare behaviour as we are insifers

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95
Q

Give a disadvantage to participant observations

A

We can become objective as an observer because we have ‘made friends’ with the participants

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96
Q

Non-participant observations

A

The observer is not a participant in the behaviour being observed

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97
Q

Give an advantage of non-participant observation

A

We remain objective as we aren’t taking part in the behaviour

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98
Q

Give a disadvantage of non-participant observation

A

We may misinterpret what we are seeing as we aren’t part of the behaviour being observed so we wont fully understand

99
Q

Structured observation

A

Recording behaviour in a systematic manner to organise out data

100
Q

Give an example of structured observation

A

A coding scheme

101
Q

Give an advantage of a structured observation

A

Results are likely to be quanitative so are easier to analyse

102
Q

Give a disadvantage of a structured observation

A

Behaviours not on our coding scheme are likely to be missed

103
Q

Unstructured observation

A

Observing all behaviour that might be relevant without any system

104
Q

Give an advantage of unstructured observation

A

Useful when we are studing behaviour that is unpredictable

105
Q

Give a disadvantage of unstructured observation

A

The behaviours that most catch our attention might not be the most important/revelent to record

106
Q

Naturalistic observation

A

Observing participants in a natural setting that would be the same if the observer wasn’t present

107
Q

Give an advantage of naturalistic observation

A

Most likely to see natural behaviour and fewer demand characteristics meaning our observations have a higher EV

108
Q

Give a disadvantage of naturalistic observation

A

Often done covertly so it has ethical issues

109
Q

Controlled observation

A

The environment is changed or controlled because of the observation. Often used because there is an IV - experiment using an observation )

110
Q

Give an advantage of a controlled observation

A

Greater control of the environment so fewer extraneous variables

111
Q

Give a disadvantage of controlled observation

A

Greater control means the experiment will be artificial so the behaviour is less natural

112
Q

Coding frames

A

A list of behavioural categories e.g tally chart

113
Q

Behavioural catogories

A

Dividing behaviour into categories in a structured observation. Good categories are precise and operationalised and will give us quantitative data

114
Q

Observer bias

A

When we lose our objectivity and see what we want to see/what we were expecting to see over what is actually there

115
Q

Observer effects

A

When the presence of an observer creates demand characteristics which influences a participants behaviour

116
Q

Time sampling

A

Recording behaviour in a regular time interval - every 5 minutes

117
Q

Give an advantage of time sampling

A

Its easier to conduct with a large group of people/with quickly changing behaviour

118
Q

Give a disadvantage of time sampling

A

We cant record behaviour that occurs between intervals meaning rare behaviour is often missed

119
Q

Event sampling

A

Using behaviour categories and a coding frame and recording behaviour from our list each time it occurs during a specified time

120
Q

Give an advantage of event sampling

A

Our results will be more representative of the usual behaviours that may not occur often

121
Q

Give a disadvantage of event sampling

A

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
Q

Self-report method

A

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
Q

Give an advantage of self-report method

A

They can give a valid measure of thoughts, feelings and opinions

124
Q

Give a disadvantage of self report methods

A

Participants might lie, show social desirability or misunderstand out questions (all reduces validity)

125
Q

Interviews

A

Usually conducted face to dace, they can be written down on the spot or tape recorded and transcribed

126
Q

Give an advantage of interviews

A

Participants can ask questions if they don’t understand

127
Q

Give a disadvantage of interviews

A

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
Q

Social desirability

A

You give a socially desirability answer and not your true answer - you lie

129
Q

Inter-rater reliability

A

the extent to which two or more raters in an observation/self report agree in the results they’ve collected

130
Q

How can you improve inter-rater reliability

A

use operationalised categories
Produce categories in a pilot study
Train raters on how to use categories

131
Q

Evaluation anxiety

A

Fear of being judged

132
Q

Unstructured interview

A

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
Q

Give an advantage of unstructured interviews

A

We can gather qualitative data so results may be richer and more in-depth

134
Q

Give a disadvantage of unstructured interviews

A

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
Q

Semi-structured interviews

A

Some questions are pre-determined but the interviewer has the freedom to follow up interesting responses

136
Q

Give an advantage to semi-structured interviews

A

We can gather qualitative data so results may be richer and more in-depth

137
Q

Give a disadvantage to semi-structured interviews

A

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
Q

Structured interviews

A

Uses a predetermined set of questions asked in the same way for each participant

139
Q

Give an advantage to structured interviews

A

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
Q

Give a disadvantage to structured interviews

A

Its hard to follow up on interesting answers because the questions are restricted and you can’t variate from them

141
Q

Correlation method

A

A relationship between two variables. They don’t look at whether one has affects the other. They use co-variables

142
Q

Give an advantage of correlations

A

We can research variables that it would be unethical to research in an experiment

143
Q

Give a disadvantage of correlations

A

We cant see cause and effect in a correlations, only a relationship between the two variables

144
Q

Correlation coefficient

A

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
Q

What are the results in a correlation coefficient

A

+1 is a perfect positive correlation
0 is no correlation
-1 is a perfect negative correlation

146
Q

Reliability

A

The consistency of our measure, research, method, findings or data collected over time. CONSISTENCY IS KEY

147
Q

Internal reliability

A

The extent to which a measure is consistent within it’s self

148
Q

Split half method of testing reliability

A

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
Q

External reliability

A

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
Q

Test-retest reliability

A

Give participants a the same test on two different occasions and compare the results

151
Q

Inter-rater reliability

A

Compare the results of two different observers/raters and check for consistency in the results

152
Q

What are some factors that can affect reliability?

A

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
Q

Alternative hypothesis - HI

A

A hypothesis that predicts the significant relationship between two covariables

154
Q

Give an example of an alternative hypothesis

A

There will be a significant correlation between the achievement in the AS psychology and attendance in the AS psychology course

155
Q

Null hypothesis - H0

A

A hypothesis that predicts there will be no significant correlation between the two covariables

156
Q

Give an example of a null hypothesis

A

There will be no significant correlation between the achievement in the AS psychology and attendance in the AS psychology course

157
Q

One tailed (directional) correlation hypothesis

A

A hypothesis that predicts a significant correlation and specifies the direction

158
Q

Give an example of a one tailed correlation hypothesis

A

There will be a significant POSITIVE correlation between attendance and grades in psychology

159
Q

Two tailed (non-directional) correlation hypothesis

A

A hypothesis that predicts a significant correlation but doesn’t specify the direction

160
Q

Give an example of a two tailed correlation hypothesis

A

There will be a significant correlation between attendance and grades in psychology

161
Q

Validation

A

The extent to which a study measures what it claims to measure

162
Q

External validity

A

Can the findings be generalised beyond the original study

163
Q

Internal validity

A

Does a study test what it claims to test?

164
Q

Face (content) validity

A

Does the test appear to measure what it intends to measure?

E.g - Hand size and IQ correlation is wrong

165
Q

Construct

A

Does the test measure the ‘construct’ it intends to measure?

166
Q

Concurrent validity

A

Does a new test give comparable results to an old established test?

167
Q

Predictive validity

A

Do the test results accurately predict future behaviour?

168
Q

Criterion validity

A

Do the test results accurately predict future behaviour?

169
Q

Population validity

A

Can we generalise the results to populations beyond those tested in the study?

170
Q

Ecological validity

A

Can we generalise the results to setting and situations beyond the setting of the study?

171
Q

Mundame realism

A

How realistic/believable is a study compared to the everyday world

172
Q

Demand characteristics`

A

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
Q

Social desirable bias

A

Occurs when participants answer questions or present themselves in a more positive light - how society wants them to act

174
Q

Researcher/observer effects

A

When the observer/researcher influences or effects a participants behaviour

175
Q

Researcher/observer bias

A

When a researcher/observer expectations influences the results

176
Q

Sampling methods

A

Some sampling methods are more likely to lead to samples with a higher/lower population validity

177
Q

Experimental design

A

Some experimental designs lead to an increased chance of demand characteristics and/or order effects

178
Q

Control of variables

A

Extraneous variables will influence whether we are testing the IV’s isolated effect on the DV’s

179
Q
A

Less than

180
Q
A

Much less than

181
Q

∝

A

It’s reducable to

182
Q

≤

A

Less than or equal to

183
Q

>

A

Greater than

184
Q

> >

A

Significantly greater than

185
Q

≥

A

More than or equal to

186
Q

≠

A

Is not equal to, doesn’t equal

187
Q

~

A

Is similar to

188
Q

Standard form

A

A way of writing down very large or very small numbers

189
Q

Decimal form

A

A fraction written in a special form

190
Q

Significant figures

A

Each of the digits of a of a number are used to express it, starting from the first non-zero number

191
Q

Primary data

A

Data collected first hand - specific to your research

192
Q

Secondary data

A

Data already collected - not specific to your research

193
Q

Quantitative data

A

Numerical data that can be statistically analysed - answers to a closed question

194
Q

Qualitative data

A

Rich, detailed, in-depth and descriptive data - responses to an open question

195
Q

Nominal data

A

Individual categories under titles, collective scores under a heading

196
Q

Give an example of nominal data

A

Age, gender

197
Q

How do you display nominal data

A

Mode, bar chart or pie chart

198
Q

Ordinal data

A

Ranking 1st, 2nd, 3rd not equal intervals

199
Q

Give an example of ordinal data

A

Grades

200
Q

How would you display ordinal data

A

Median, mode, bar chats, pie chars and frequency tables

201
Q

Interval data

A

Continuous data where differences between intervals are equal - individual scores, set scored

202
Q

Give an example of interval data

A

Temperature, time taken to complete work

203
Q

How would you display interval data

A

Mode, median, mean, bar chart, pie chart, histograms and scatter graphs

204
Q

Ratio data

A

Has an absolute zero and intervals are equal

205
Q

Give an example or ratio data

A

Money, time

206
Q

How would you display ratio data

A

Mode, median, mean, bar chart, pie chart, histogram and scatter graphs

207
Q

Measures of central tendency

A

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
Q

Mode

A

Adding all your values together and dividing by the number of values

209
Q

Give an advantages of mode

A

It includes every value within your data

210
Q

Give a disadvantage of mode

A

Very sensitive to outliers, particularly with a small data set and it cant often be used for nominal data

211
Q

Median

A

Median is the middle value

212
Q

Give an advantage of median

A

It is less affected by extreme values and it can be used on interval and ordinal data

213
Q

Give a disadvantage of median

A

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
Q

Mode

A

Most frequent score

215
Q

Give an advantage of mode

A

Can be used for any data set and is not affected by extreme scored/anomolies

216
Q

Give a disadvantage of mode

A

Various values that meet the criteria it can be bi-modal

A mode may not be described where most data is concerned

217
Q

Measures of dispersion

A

This value describes how spread out our data us

218
Q

Variance

A

How spread out the data is around the mean

219
Q

Range

A

The difference between the highest and lowest numbers. A large range means there’s a lot of variability in the data

220
Q

Standard deviation

A

The square root of the variance

221
Q

Ratios

A

Shows the relation between two quantaties

222
Q

Percentages

A

Representation of a rate or number out of 100

223
Q

Fractions

A

A numerical quantity that is not a whole number - 1/4

224
Q

Do a bar chart’s bars touch or not?

A

They don’t touch because they’re not related

225
Q

Do a histogram’s bars touch or not?

A

Yes because its a continuous scale

226
Q

Probability

A

The likely hood that something will happen between 0 and 1

227
Q

Observed value

A

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
Q

Which test will follow a normal distributon curve

A

Parametric test

229
Q

Statical significance

A

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
Q

Type 1 error

A

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
Q

Type 2 error

A

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
Q

Peer review

A

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
Q

What independent measures design do we use for nomianal data

A

Chi squad

234
Q

What independent measures design do we use for ordinal data

A

Mann Whitney U

235
Q

What independent measures design do we use for interval/ration data

A

Unrelated + test

236
Q

What repeated measures design do we use for nomianal data

A

Binominal sign test

237
Q

What repeated measures design do we use for ordinal data

A

Wilcoxon

238
Q

What repeated measures design do we use for interval/ration data

A

Related + test

239
Q

What test for correlation do we use for ordinal data

A
240
Q

What test for correlation do we use for nominal data

A

Spearmans rank

241
Q

What test for correlation do we use for interval/ration data

A

Pearsons product moment

242
Q

Define validity

A

Is there something getting in the way of measuring what they wanted to measure? Extraneous variables?

243
Q

Define reliability

A

Is the study replicable? How consistent is the measuring device? Does the study have a standardised procedure?

Psychology (6 decks)

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