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A-Level Psychology > Research Methods > Flashcards

Research Methods Flashcards

1
Q

Informed consent

A

Ppts should be told as much as they can be about the study so they can make a decision as to whether or not to partake.

In some cases, however, PPts cannot make such decisions because they may not be able to undertsand. In such cases, the consent of the parent or guardian should be taken. Or the ethics committee should be contacted.

Some issues with this is that the researchers may not know what will happen and ppts may not show natural behavior.

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2
Q

Deception

A

Misleading the ppts or withholding the true aim of the study because the ppts are likely to object or show unease once debriefed.

It should only be used as the last alternative, approval should be gotten from the ethics committee, there must be a debrief and prior general and presumptive consent should be gotten.

Deception may ensure natural behavior and avoid the Hawthorne effect. Effective debriefing may reduce harm caused by deception.

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3
Q

Protection from harm

A

Ppts may not be exposed to great psychological or physical rish than their normal life experiences.

There must be a debrief with true aim of the the study, right to withhold data, reassurance of normal behavior and offering counsel

Sometimes harm is necessary

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4
Q

Right to withdraw

A

Ppts must be made aware that they are allowed to leave at any time and refuse permission to have their data used.

Ppts must be clearly informed of this and procedures should be put in place for this to happen.

It may lead to incomplete experiments

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5
Q

Confidentiality

A

Information about ppts is protected by data protection act and they must be identifiable in research.

Ppts are given numbers or referred to by initials.

Initials may not always be confidential.

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6
Q

Privacy

A

This involves not invading people’s personal lives which may be difficult if ppts are unaware they are being watched.

Ppts should only be observed in public.

Some very important issues only take place in private. Hawthorne effect.

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7
Q

Prior general consent

A

Obtaining prior consent from a ppt to see if they would be okay partaking in a study involving deception.

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8
Q

Presumptive consent

A

Taking a random sample of the population and introducing them to the research including deception and if they agree, this can be generalised to the general population.

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9
Q

Retrospective consent

A

Once the true nature of the study has been revealed, the ppt has the right to withdraw

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10
Q

Variable

A

Any factor, trait or condition that can exist in differing amounts or types

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11
Q

Independent Variable

A

One that is changed by the researcher

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12
Q

Dependent Variable

A

One that is affected by the independent variable

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13
Q

Extraneous Variable

A

Potential variable that can affect the invetsigation

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14
Q

Laboratory Experiments

A

They look for the effect IVs have on DVs in a controlled, artificial environment where the participants are allocated randomly to experimental conditions

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15
Q

Strengths of lab experiments

A

High control over extraneous variable so causation can be asserted
Reliable results as created conditions can be replicated
Variables can be measured accurately and empirically

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16
Q

Weaknesses of lab experiments

A

Lacks ecological validity because it is artificial
High risk of demand characteristics
Experimental bias; how researchers interact with ppts

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17
Q

Field Experiments

A

They are conductded in a natural setting but the IV is still altered by the researcher

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18
Q

Strengths of field experiments

A

Higher ecological validity
Demand characteristics are less of an issue

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19
Q

Weaknesses of field experiments

A

More extraneous variables
Lack of informed consent
Poor reliability
Sample bias because ppts are not randomly allocated

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20
Q

Natural Experiments

A

When researchers investigate a naturally existing change as their IV

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21
Q

Strengths of natural experiments

A

High ecologoical validity
Less demand characteristics
Can be used in situations where manipulating the IV would be unethical

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22
Q

Weaknesses of natural experiments

A

Sample bias
Extraneous variable reduces causal effects
Lack of informed consent

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23
Q

Quasi experiments

A

IV is alredy existing

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24
Q

Strengths of quasi experiments

A

They can be carried out under controlled conditions
Allows areas of research otherwise impossible

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25
Q

Weakness of quasi experiments

A

No control over assignment of ppts to independent variable

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26
Q

Questionnaires and its different formats

A

They are written self-report technique where ppts have a set number of answers to respond to.

They can be with closed (where there is a predetermined set of data and which produces quantitative data which may lack detail but is easy to analyse) or open questions (where there is no restriction on how ppts can reply which is rich in detail but hard to analyse)

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27
Q

Types of questionnaires

A

Likert scale: indicate agreement on a scale of 5 points
Rating scale: identify a value that represents their strength feeling about a particular topics
Fixed choice option: list of possible options and respondents are required to indicate what applies to them

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28
Q

Strengths of questionnaires

A

They are relatively cheap and quick to gather large amounts of data
Ppts are more likely to be honest because they are anonymous

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29
Q

Weaknesses of questionnaires

A

Social desirability bias
Sample bias may be an issue as only certain types of ppl answer them
Some questions may be leading
Response bias; e.g acquiescence bias due to an overuse of jargon or double-barrelled questions which either use double negatives or 2-in-1 questions
Questions may be misunderstood

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30
Q

Interviews and its different types

A

They are self-report techniques that involve the researcher asking questions and recording the answers either on a one-to-one basis or with multiple ppts are the same time.

Structured: list of questions rigidly stuck to, known as interview schedule which allow for easy replication and generalised findings.

Unsturctued: list of topics of questions with extra flexibility which gives more detailed discussion which does not allow for replication or generalisation

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31
Q

Strengths of interviews

A

They gather more rich and detailed information than questionnaires
They are best suited for complex or sensitive issues
They can be used as part of a prior study to gather information prior research

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32
Q

Weaknesses of interviews

A

A lot of time and expenses goes into training interviewers
Social desirability bias
Detailed data may be difficult to analyse
They require ppts to have basic competencies such as memory which could reduce the sample size.

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33
Q

Types of observations

A

Controlled, Naturalistic, Participant and Non-Participant Observations, and Covert and Overt Observations

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34
Q

Controlled Observations

A

They are likely to be carried out in an artificially controlled environment, with a standardised procedure and a behaviour schedule (agreed scale of coding behavior) and observing behavior in categories e.g Strange Situation

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35
Q

Strengths of controlled Observations

A

Easily replicated so easy to test for reliability
Quantitative to easy and quick to analyse so less time-consuming
Fairly easy to conduct so a large sample can be obtained to be generalised to a large population

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36
Q

Weakness of Controlled Observations

A

Lack validity due to demand characteristics and ecological validity

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37
Q

Naturalistic Observation

A

Studying natural behaviour of ppts in natural surroundings which could use behavioural categories or not e.g William’s study of aggression after intro to tv

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38
Q

Strength of a naturalistic observation

A

Greater ecological validity

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39
Q

Weaknesses of naturalistic observation

A

Micro scale so not representative so not generalisable
Less reliable so difficult to replicate
Need to be trained to recognise psychologically significant
Less able to manipulate variables so causation uncertain

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40
Q

Participant observation

A

One where the researcher joins the group and observes their activities by writing notes and reflecting later on e.g Rosenhan reliability of diagnosis of schizo

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41
Q

Strength of participant observation

A

Close proximity means unlikely to overlook behaviour–increased insight

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42
Q

Weakness of participant observation

A

Hawthorne or investigator effect

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43
Q

Non-participant observation

A

The psychologist observed activities but does not take part in them e.g Strange Situation

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44
Q

Strength of non-participant observation

A

Ppt reactivity and investigator effects less likely

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45
Q

Weakness of non-participant observation

A

Rsr might overlook or miss interesting behaviour

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46
Q

Covert and overt observation

A

Covert is when the rsr real identity and purpose is kept concealed
Overt is when the rsr revels their true identity and purpose and asks for permission to observe

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47
Q

Strength and weakness of covert observation

A

Increased validity due to increase of natural behaviur
Ethical Issues due to lack of consent

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48
Q

Strength and weakness of overt observation

A

Ethically acceptable
Low internal validity due to influenced behaviour

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49
Q

Structured and unstructured observation

A

Structured clearly defines and focuses on behaviours linked to study
Unstructured writes all that’s seen

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50
Q

Strength and weaknesses of unstructured observation

A

Rich qualitative data which increases internal validity

Time consuming to complete, analyse and train researchers
Risk of observer bias reducing reliability

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51
Q

Strengths and weakness of structured observation

A

Time efficient due to qualitative data
Easier to replicate because its reliable

It may lack important details

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52
Q

Behavioural categories

A

When target behaviour is broken up into components that are observable and measureable

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53
Q

Strength of behavioural categories

A

The result is reliable and quantitative and can be used to identify trends and patterns

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54
Q

Weaknesses of behavioural categories

A

Researchers may interpret information differently leading to unreliable results
Categories need to be valid
Significant behaviour may occur that is missing from categories
Time is required for observers to train and practise

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55
Q

Types and explanation of sampling methods

A

Event sampling: the number of times specific event or behavior occurs during the observation
Time sampling: any behaviour being demonstrated at a specific time interval

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56
Q

Strength and weakness of event sampling

A

Behavior could occur infrequently and could be missed by time sampling
It might miss other important complex behaviours

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57
Q

Strength and weakness of time sampling

A

Useful in reducing the amount of observations needed to be taken
Might miss infrequent behaviours

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58
Q

Inter-observer reliability

A

The idea that two researchers must be consistent and record similar data for unbiased and objective results.

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59
Q

Necessities for Inter-observer reliability

A

They must:
- familiarise themselves with the categories
- observe the same thing simultaneously in a pilot study
- analyse the collect data by correlating each pair of results

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60
Q

Correlation

A

A type of non-experimental research that measures the strength and direction of a relationship between co-variables

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61
Q

Types of correlations

A

Positive: change in the same way
Negative: change in different ways but there is a pattern
No correlation: no pattern

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62
Q

Strengths of correlations

A

They are useful as a preliminary research technique to identify a link before further research
Can be used to research unethical topics
Provides a precise and quantifiable measure of how two variables are related
Quick and easy to carry out

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63
Q

Limitations of correlations

A

Explains why variables are related but not why
It does not establish causation
Does not take into account third-factor variable which impacts both variables so they don’t affect each other

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64
Q

Correlation coefficient

A

The strength of a correlation which is between 1 and -1

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65
Q

What is a strong, moderate and weak correlation coefficient?

A

Strong: 0.7 or above
Moderate: 0.4 or above
Weak: 0.1 or above

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66
Q

Content Analysis

A

Systematically reviewing qualitative information to produce a conclusion and test a hypothesis which can be done by coding or thematic analysis

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67
Q

Strengths of a content analysis

A

Data is often easily available
Cheap and easy
Well-designed coding units means valid and easily reliable
Few ethical issues
Real-life sources give high external validity
Can produce quantitative data which is easy to analyse
Qualitative thematic analysis which is rich in detail and meaning

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68
Q

Weaknesses of content analysis

A

Thematic analysis can be time consuming
Element of subjectivity required to interpret data
It could show possible experimenter bias and reduce reliability and internal validity
It does not give any causal explanation

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69
Q

Coding analysis

A

Qualitative data is place into categories based on coding units, how many times a word or phrase appears in a text

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70
Q

Thematic analysis

A

Wider themes or idea are present and used to make decisions

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71
Q

Case studies

A

A very detailed investigation of an individual or small group of people usually regarding an unusual phenomenon or biographical event of interest to a research field

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72
Q

How are ppts interviewed in case studies

A

Interviews, family history, questionnaires, autopsies, cognitive tests, school records, observations, experiments and longitudinal studies

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73
Q

Strengths of case studies

A

Rich yield of data
Can give insight into how something functions
Longitudinal study can study change over time
It could conflict with current theories and stimulate new, better paths for research

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74
Q

Limitations of case studies

A

Small sample size cannot be generalised
Little control over variables
Poor reliability as replication is unlikely
Researcher may become so involved that they exhibit bias which reducing how factual it is

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75
Q

Reliability

A

The consistency of findings of research which often depends on how replicable it is

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76
Q

Internal reliability and how it can be checked

A

The consistency of results across items within a test
It can be checked by split-half method; items or questions and data collected is split randomly in half and compared to see if results taken from each part of the measure is similar

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77
Q

External reliability

A

The extent to which a measure varies from one use to another e.g experiment carried out on two different days

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78
Q

How to assess external reliability

A

Inter-rater reliability: the degree to which different raters give consistent estimates of the same behaviour
Test-retest reliability: used to assess the stability of a test over time by giving ppts the same test on different occasions

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79
Q

Ways to improve reliability (self-report)

A

Rewrite questions that give inconsistent data
Structured approach as they are more specific
Use the same interviewer to reduce bias
Trained interviewers

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80
Q

Ways to improve reliability (experiments)

A

Operationalised DV and IV
Standardised procedure
Controlled extraneous variable

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81
Q

Ways to improve reliability (observations )

A

Train observers in observational techniques
Operationalised behavioural categories

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82
Q

Validity

A

Refers to whether a test actually measures what is claims or whether a theory really explains the phenomenon

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83
Q

Internal Validity

A

Whether the effects observed in the study are due to the manipulation of the IV and not other factors

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84
Q

External Validity

A

The extent to which findings can be generalised beyond research findings

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85
Q

Population validity

A

How far the results can be generalised to other groups

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86
Q

Ecological validity

A

To what extent the results can be generalised to real-life settings

87
Q

Temporal validity

A

The extent to which results can be generalised to other time periods

88
Q

State and explain how to assess internal validity

A

Face Validity: looking at the test at face value and using intuition to see whether the test is appropriate for measuring phenomenon

Concurrent Validity: a measure of how well a particular test correlates with previous validated measure; having a high concurrent validity of 0.8

89
Q

State how to assess external validity

A

Population, ecological and temporal validity

90
Q

How to improve validity (experimental design)

A

Using a control group
Standardised procedure
Blind/double blind
Clear IV or DV (operationalised)
Reduce EV or nuisance variable
Keep true aim covert to reduce demand characteristics
Use of matched pairs or repeated measures to reduce ppt variables

91
Q

How to improve validity (questionnaires)

A

Lie scale (varied comments and contradictory statements to check consistency of results)
Anonymity reduces demand characteristics or social desirability bias

92
Q

How to improve validity (observations)

A

Covert observations
Behavioral categories
Naturalistic

93
Q

How to improve (qualitative methods)

A

Triangulation: use of self-report techniques and observations before reaching a conclusion
Interpretive validity: reporting or use of direct quotes

94
Q

Experimental design types

A

Independent groups, matched pairs and repeated measures

95
Q

Independent groups

A

Different ppts are randomly allocated to each conditions of the independent variable ensuring they have an equal chance and reducing investigator bias

96
Q

Order effects

A

When a ppt becomes tired, bored or fed of with repeating the same conditions or they begin to guess the true aim of the experiment

97
Q

Advantage of independent group

A

Reduces order effects as they are in one condition only

98
Q

Disadvantages of independent group

A

Ppt variables, such as variations in age or sex, may affect results
More ppl are needed than in other designs

99
Q

Repeated measures

A

The same groups of ppts take part in each condition of the independent variable

100
Q

Advantages of repeated measures

A

Fewer people are needed which saves time
Reduces effect of ppt variables

101
Q

Disadvantages of repeated measures

A

Order effects
Demand Characteristics

102
Q

Counterbalancing

A

Alternating the order in which ppts perform the different conditions of the experiment

103
Q

Matched pairs

A

Ppts are matched on key characteristics and one member is allocated to one test condition

104
Q

Advantages of matched pairs

A

Reduces ppt variable as ppts are similar
Avoids order effects so counterbalancing is not necessary

105
Q

Disadvantages of matched pairs

A

Very time consuming to find closely matched pairs
Impossible to match people up exactly

106
Q

Aim

A

Identifies the purpose of the investigation

107
Q

Hypothesis

A

A precise, testable statement of what the outcome of the study could be, proposing the relationship between two operationalised variables

108
Q

Types of hypotheses

A

Null hypothesis: assumes no relationship between IV and DV
Alternative hypotheses: assumes a relationship either a specific (Directional or one-tailed) or not specific (Non-directional or two-tailed)

109
Q

Pilot study

A

Small-scale trial that runs off the actual investigation using a smaller sample size

110
Q

How to use pilot studies to improve self-report methods or observational studies

A

Self-report: try out questions in advance and remove ambiguous or confusing ones
Observation: check behavioural categories

111
Q

Advantages of pilot study

A

Identify potential issues in procedure that saves money and time in the long run
Removes extraneous variables and increases internal validity
Maintaining control so the study is more reliable

112
Q

Sample

A

A group of ppl who take part in an investigation

113
Q

Sampling

A

The process of selecting ppts from the target population

114
Q

Target population

A

The total group of individuals from which the sample might be drawn

115
Q

Generalisability

A

The extent to which findings from the research can be applied to the target population

116
Q

Purpose of sampling

A

Impossible to study every single individual so sample is representive which is more realistic

117
Q

Random sampling

A

Each member of the target population has a chance of being selected

118
Q

Sample frame

A

Data on target population to select from

119
Q

Advantage of random sampling

A

No researcher bias, more representative population

120
Q

Disadvantages of random sampling

A

Can be time consuming e.g sourcing different lists
Some may refuse; volunteer bias

121
Q

Systematic sampling

A

Ppts are selected at fixed intervals from the sample frame e.g every fifth ppt

122
Q

Advantage of systematic sampling

A

No researcher bias, more representative

123
Q

Disadvantages of systematic sampling

A

Can be time consuming
Might lead to volunteer bias

124
Q

Stratified sampling

A

Reflects main groups of target population

125
Q

Strata

A

Subgroup of target population

126
Q

Advantages of stratified sampling

A

Generalisable if strata is accurate
Removes researcher bias

127
Q

Disadvantage of stratified sampling

A

Time consuming due to requirement of accurate information

128
Q

Opportunity sampling

A

Researcher selects whoever is available at the time

129
Q

Advantage of opportunity sampling

A

Quick and easy way of selecting information

130
Q

Disadvantage of opportunity sampling

A

May not be representative and some research bias

131
Q

Volunteer sampling

A

Ppts put themselves forward

132
Q

Advantage of volunteer sampling

A

Easy, quick and cheap

133
Q

Disadvantage of volunteer sampling

A

Volunteer bias, not representative which reduces population validity

134
Q

What are the two main variables in an experiment?

A

Independent variable (the one being manipulated by the researcher) and the dependent variable (the one affected by the IV)

135
Q

What are the unwanted variables

A

Extraneous or nuisance variables: variables that are not the IV that affect the DV

136
Q

Types of extraneous variables

A

Participant variables: features of ppts
Situational variables: features of experiment or setting e.g temperature
Demand charateristics: clues that imply aim
Experimenter bias: any intentional or unintentional influence of the investigator’s behavior which affects the investigation

137
Q

Confounding variables

A

Change systematically with the IV and affects the DV

138
Q

Randomisation

A

Making elements of the study unpredictable to reduce any extraneous variables e.g random words for recall or random conditions

139
Q

Standardisation

A

Using exactly the same procedure and instructions for all ppts in a research study to reduce extraneous variables and increase replication

140
Q

Single blind vs double blind

A

Researcher knows IV groups but ppt doesn’t
Neither researcher nor IV knows IV groups

141
Q

Qualitative data

A

Expressed in written description of thoughts and feelings from accounts of interviews or diaries

142
Q

Strengths of qualitative data

A

Rich in detail
Higher in validity as it provides more meaningful insight of ppts view

143
Q

Weaknesses of qualitative data

A

Can be difficult to analyse data and occuring patterns

Conclusions could be subjective

144
Q

Quantitative data

A

Expressed numerically and can be analysed statistically

145
Q

Strengths of quantitative data

A

Simple to analyse
Easy comparison between groups
Less biased numerical data

146
Q

Weaknesses of quantitative data

A

May fail to represent real life
May not include thoughts and feelings

147
Q

Primary data

A

Collected for the purpose of the investigation by the researcher

148
Q

Strength and weakness of primary data

A

Specifically designed for experiment
Time-consuming

149
Q

Secondary data

A

Data that already exists collected for the research

150
Q

Strengths of secondary data

A

Easy and cheap
No need for additional collection

151
Q

Weaknesses of secondary data

A

Outdated
Incomplete
May not match needs of the investigation

152
Q

Advantage and disadvantages of mean

A

Most sensitive measure of central tendency as it is made up of all scores in data set

Anomalous data could distort it
May not make sense using discrete units

153
Q

Advantage and disadvantages of median

A

Less affected by extreme scores than the mean

Less sensitive than the mean as it does not reflect all data
Not suited for smaller data sets

154
Q

Advantages and disadvantage of mode

A

Only way of describing data from categories
Normally unaffected by extreme scores

May not be central measure as it does not represent all data

155
Q

Range

A

The difference between the highest and lowest scores in a data set, with the addition of 1

156
Q

Advantage of range

A

Provides direct information on the data which is easy to analyse

157
Q

Disadvantages of range

A

Affected by extreme values
Does not take into account all the data
Doesn’t consider the distribution of data within range

158
Q

Standard variation

A

How much variation from the average exists

159
Q

Advantage and disadvantage of standard variation

A

More precise measure which takes all values into account
Can be affected by anomalies if there are a few (not just one)

160
Q

Measures of Central tendency

A

Mean, median and mode

161
Q

Measures of dispersion

A

Range and Standard Deviation

162
Q

Discreet Data

A

Exact figures which can be counted and can be put into categories with no relationship

163
Q

Continuous data

A

Measurable values representing a range of information on a scale with relationship between data

164
Q

Types of graphs

A

Bar graphs, histograms, line graphs, scattergrams and tally charts

165
Q

Bar chart

A

Used for discreet data, where the IV is plotted on the x axis and the DV on the y axis and with a title where both are operationalised

166
Q

Histograms

A

Used for continuous data and the bars can be joined

167
Q

Line graph

A

Used for continuous data with a curve of best fit, showing change over time on the x axis

168
Q

Scattergrams

A

For correlations with a line of best fit

169
Q

Distribution Curve

A

One used to represent frequency data (on the x axis) in a population or sample

170
Q

Normal distribution

A

A classic bell-shaped curve with the mean, median and mode in the middle and about 68% falling with the midpoint, then 95% in the whole curve as the tails never touch the x axis for more extreme figures

171
Q

Positive distribution

A

The tail is to the positive side with the order of value being: mode, median and mode; here most people get low scores

172
Q

Negative distribution

A

The tail is to the negative side with the order of values being mean, median and mode where most people get high scores

173
Q

Peer review

A

Takes place before a study is published to ensure that it is of high quality by subjecting it to scrutinisation by a small group of experts in a particular field unknown to the author or researcher

174
Q

Aims of peer review

A

To allocate research funding
To validate the quality and relevance of research
To suggests amendments and improvements

175
Q

Evaluative points of peer review

A

Anonymous peer reviews; give overly critical reviews to protect prestige; naming reviewers to avoid this; valid research may be blocked—Anonymity could lead to more honest opinions

Publication Bias; more likely to publish one with results than null results; file drawer effect; important findings not published and limitation of possible hypotheses

Buried groundbreaking research; expert reviewers are invested in theories, suppress opposition to mainstream theories; new theories suppressed; important findings may not be published

176
Q

The Economy

A

The consumption and production of goods within a country measured as a currency value

177
Q

The implication of psychological findings for the economy

A

What we can learn from research that can influence, benefit or devalue our economic prospoerity

178
Q

Impacts of economic implications

A

Development of treatments for mental illnesses (reduced absences at work), e.g systematic desensitisation

Further research into important topics such as role of the father (both parents can provide emotional support, more flexibile working arrangements)

Improving testimonies in court e.g accurate EWT reduces expenses on wrongful arrests

Drugs for dementia saves money than therapy

Social changes such as campaigning to reduce drunk driving and smoking

179
Q

What are the features of science

A

Empirical evidence
Objectivity
Replicability
Theory Construction
Hypothesis testing
Falsifiability
Scientific Paradigms

180
Q

Empirical methods

A

Using direct observations or experiments rather than unfounded beluefs to look for facts

181
Q

Objectivity

A

Empirical data should not be affected by expectations or opinions of the researcher as they are conducted in controlled conditions and measured concepts are operationalised

182
Q

Replicability

A

To what extent an experiment can be repeated to get similar results by different groups of people to see if similar behaviour is observed, ensuring the theory is generalisable

183
Q

Theory construction

A

Explanations must be constructed to make sense of the facts to predict behaviours or natural phenomena using inductive or deductive reasoning

184
Q

Inductive Reasoning

A

A theory is formed from an observation where a pattern is noted

185
Q

Deductive Reasoning

A

A theory is formed first then an hypothesis and then an observation is conducted to confirm it

186
Q

Hypothesis testing

A

Theories must be able to generate testable expectations or it requires modification

187
Q

Falsifiability

A

The idea that a theory must be able to be proved false by observation or experimentation

188
Q

Paradigm

A

Unifying theory which may shift when a new theory is found commonly accepted by member of a discipline or group

189
Q

Three Stages of scientific discipline

A

Prescience: range of views and no general paradigm
Normal science: generally accepted paradigm and research within discipline
Revolutionary science: paradigm shift; assumption and ways of studying language change

190
Q

Paradigm shift

A

Describes a change in view and new way of investigation

191
Q

Scientific Paradigm

A

An idea by Thomas Kuhn that all science must have a unifying theory, but social sciences, such as psychology, do not

192
Q

Features of reporting a psychological investigation

A

Title: clear and precise statement on investigation
Abstract: short summary of study including APFC which appears first but is written last
Introduction: review of theories and reason for study and funnel technique which started off broad but is later narrowed down
Methods: should be clear and detailed for replication including ppts, design, apparatus and procedure
Results: descriptive statistics (summarised data in graphs or tables) and inferential statistics (whether or not research is significant and hypothesis is accepted)
Discussion: summary of findings, real-life applications and practical and theoretical implications
References
Consent form

193
Q

Formats of references

A

Name of researcher, Year, Study, Journal Title, Volume Numbers and Page Numbers

Author, Date, Book Title, Place of Publication and Publisher

194
Q

Format of consent form

A

Dear ppt,
require ppt agreement
space to sign, date and name
no pressure to consent, right to withdrawal, confidential and anonymous
experiment details

195
Q

Probability

A

The likelihood an event will happen, expressed as a number between 0 and 1

196
Q

Statistical Significance

A

Discover if results are significant; not likely to have occurred through change using levels of 10%, 5% or 1% (or 0.1% in stringent conditions)

197
Q

What happens when a result is significant or insignificant?

A

Significant: reject the null hypothesis
Insignificant: accept the null hypothesis

198
Q

What level of significance is often used

A

5% or 0.05; 1 in 20 results could have occurred due to chance

199
Q

Nominal data

A

Data that is mutually exclusive and with no numerical significance

200
Q

Ordinal data

A

Data in which the order is significant but there is no clear difference between each one, typically meausring non-numerical concepts

201
Q

Interval data

A

Numerical scales in which we know the order and the exact difference between values

202
Q

Test of Difference vs Test of Correlation

A

Difference: investigation that measures the difference between two conditions after manipulation of the IV

Correlation: investigation into the relationship between two co-variables

203
Q

Unrelated design

A

Independent groups

204
Q

Related design

A

Repeated measures and matched pairs

205
Q

Statistical tests

A

Chi-squared, Sign Test, Chi-squared,
Mann Whitney, Wilcoxon, Spearman’s rho,
Unrelated t-test, Related t-test, Pearson’s r

206
Q

Parametric meaning and tests

A

Level of measurement if interval and the measure of central tendency is mean.

Unrelated t-test, Related t-test and Pearson’s r

207
Q

Non-parametric tests

A

Levels of measurement are ordinal or nominal and median and mode are used as the measures of central tendency.

Chi-squared, Sign test, Mann-Whitney, WIlcoxon, Spearman’s rho

208
Q

How to find whether or not a set of data is significant using the sign test

A

Find the calculated value and n number and use both to find the critical value. If critical is more than or equal to calc value, it is significant

209
Q

The rule of greater r

A

Any statistical test with the letter r in the name is where the calc value needs to be greater than or equal to the critical value

210
Q

Type 1 error

A

A situation when an assumption is when that findings show something that they don’t; rejecting the true null hypothesis and accepting wrongly the alternative hypothesis both due to chance

211
Q

Causes of type 1 error

A

P-value too high or lenient, increasing the possibility that results were due to chance Having smaller sample sizes
The probability of making a type 1 error = alpha; using lower level for alpha (level of significance; 0.05) = less likely to detect a true difference is one exists

212
Q

Type 2 error

A

Missing something that is actually happening; falsing accepting the null hypothesis and rejecting the alternative hypothesis by assuming the results were due to chance

213
Q

Causes of type 2 error

A

P-value is too stringent (0.01) even in necessary situations such as testing new drugs
The probability of making a type 2 error = beta; ensure test has enough power by having a larger sample since to detect a pract difference when it exists.

A-Level Psychology (6 decks)

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