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RMs Flashcards

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1
Q

Operationalising Variables

A

Any method in which a person is asked to state or explain their own feelings, opinions, behaviours and experiences related to a given topic.

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2
Q

Questionairre

A

A set of written questions (sometimes called items) used to access a persons’ thoughts/experiences

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3
Q

Strengths of questionnaires

A

+ Cost effective

+ Can gather large amounts of data quickly

+ Can be completed without the researcher being present

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4
Q

Single-blind review

A
  • usual form of peer review

- involves the names of reviewers not being revealed to the researcher

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5
Q

Weaknesses of questionnaires

A
  • Can produce response bias
  • P.ps may misunderstand the question or read it incorrectly
  • Demand Characteristics / Social Desirability may occur
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6
Q

Open review

A

the reviewers and the researcher being known to each other

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7
Q

Double-blind review

A

both the reviewers and the researcher are anonymous

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8
Q

Questionnaire construction

A

Aims, length, previous questionnaires, question formation, pilot study, measurement scale

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9
Q

Advantages & Disadvantages of an Open Question

A

+ Get more information

+ Produces qualitative data - depth and detail

  • People can miss them out as they can’t be bothered to answer them
  • Harder to analyse
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10
Q

Closed Question

A

Questions with a fixed answer/ the choice of response is determined by the question setter.

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11
Q

Advantages & Disadvantages of a Closed Question

A

+ People have to same perception of the Q&A

+ Quick and easy to answer

+ Quantitative data is easier to analyse

  • Not detailed or in depth answers
  • Don’t find out the meaning behind the answer
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12
Q

Interview

A

A live encounter (face to face or on the phone) where one person asks a set of questions to assess an interviewees thoughts/experiences. They can be structured, semi structured or unstructured.

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13
Q

Structured Interview

A

Made up of pre-determined questions and are asked in a fixed order. Basically like a questionnaire but conducted face to face.

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14
Q

Unstructured Interview

A

Works like a conversation. There are no set questions. There is a general aim that a certain topic will be discussed and interaction tends to be free flowing.

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15
Q

Semi-structured Interview

A

There is a list of questions that have been worked out in advance but interviewers are also free to ask follow up questions when they feel it is appropriate.

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16
Q

Strengths & Weaknesses of Structured Interview

A

+ Straight forward to replicate

+ Reduces differences between interviews

+ Easier to analyse

+ Get answers you’re looking for

  • Get less information as P.ps can’t deviate from the point
  • Don’t find out people’s worldwide views
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17
Q

Strengths & Weaknesses of Unstructured Interview

A

+ Can get more detailed answers as people can elaborate

+ More flexible as you can gain insight

  • Not easy to replicate
  • Not easy to analyse as you get irrelevant information
  • Experimenter effects can occur
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18
Q

Design of interviews

A

Gender and age, ethnicity, personal characteristics and adopted role

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19
Q

Leading Questions

A

Encourages P.ps to give a particular answer e.g don’t you think…?

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20
Q

Ambiguity

A

Questions which can be interpreted in various ways. They can mean different things to different people.

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21
Q

Loaded Questions

A

They are questions which contain emotive language which is likely to produce an emotional reaction in the respondent.

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22
Q

Double-barreled Questions

A

They contain two options within a single question.

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23
Q

Aim

A

A general statement that the researcher intends to investigate.

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24
Q

Hypothesis

A

A detailed statement which is clear, precise and testable that states the relationship between variables being tested.

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25
Q

Directional Hypothesis

A

The researcher makes it clear what difference is anticipated between the 2 conditions or groups.

(One tailed).

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26
Q

Non-directional Hypothesis

A

Simply states that there is a difference but not what the difference will be.

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27
Q

Null Hypothesis

A

There will be no relationship between the 2 variables.

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28
Q

Meta-analysis

A

A particular form of research method that uses secondary data. Data from a large number of studies which have involved the same research question and method are combined.

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29
Q

Qualitative Data

A

Data that describes meaning and experiences which is expresses in words e.g. case studies, interviews and observations.

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30
Q

Primary Data

A

Information that has been obtained first hand by the researcher. It is also known as field research.

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31
Q

Secondary Data

A

Information that has already been collected by previous researchers. It is also known as ‘desk research’ and can be found in journal articles, books or websites.

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32
Q

Ethical issues

A

the rules governing the conduct of researchers in investigations

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33
Q

Informed Consent

A

Participants should be told what they are letting themselves in for. Only then they are in a position to give informed consent. If under 16 consent must be obtained from their parents.

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34
Q

Deception

A

Information is withheld from participants: they misled about the purpose of the study and what will happen during it.

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35
Q

Right to Withdraw

A

Participants should be told this at the start of the research. No attempt should be made to encourage them to remain.

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36
Q

Protection from harm

A

Participants should not be put through anything they wouldn’t normally be expected to.

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37
Q

adequate briefing/ debriefing

A

all relevant details of a study should be explained to participants before and afterwards

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38
Q

Observational research

A

observations are only made in public places where people might expect to be observed by strangers

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39
Q

incentives to take part

A

participants should not be offered bribes or promised rewards for their participation

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40
Q

Variable

A

Any “thing” that can vary or change with in an investigation. They are generally in experiments to determine if changes in one result in changes to another.

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41
Q

Independent Variable - IV

A

An aspect of the experimental situation that is manipulated by the researcher or changes naturally so the effect on the DV can be measured.

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42
Q

Dependent Variable - DV

A

The variable that is measured by the researcher. Any result/change on the DV should be caused by the change in the IV.

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43
Q

Operationalising Variables

A

The process of devising a way of measuring a variable. It is a clear statement of what the variable is.

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44
Q

Lab Experiment

A

An experiment that takes place in a controlled environment where the researcher manipulates the IV and records the effect on the DV while maintaining strict control of extraneous variables.

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45
Q

The Criteria for a Lab Experiment

A

1) The IV is manipulated by the researcher to produce a change in the DV
2) All other variables that might influence the results i.e. extraneous variables are held constant or eliminated
3) Participants are randomly allocated to a condition.

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46
Q

Advantages of a Lab Experiment

A

+ Can establish cause and effect

+ Few if any extraneous variables

+Easy to replicate

+High internal validity

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47
Q

Disadvantages of a Lab Experiment

A
  • Lacks ecological / external validity
  • Demand characteristics can occur
  • Behaviour in a lab is often different
  • Experimenter effects can occur
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48
Q

Reliability

A

the extent to which a test or measurement produces consistent results

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49
Q

Validity

A

the extent to which results accurately measure what they are supposed to measure

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50
Q

Internal validity

A

concerns whether results are due to manipulation of the IV and have not been affected by confounding variables

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51
Q

External validity

A

refers to the extent to which an experimental effect (results) can be generalized to other settings

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52
Q

Face validity

A

assessing validity and involves the extent to which items look like what a test claims to measure

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53
Q

Concurrent validity

A

assesses validity by correlating scores on a test with another test known to be valid

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54
Q

The scientific process

A

Popper- a means of acquiring knowledge based on observable, measurable evidence

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55
Q

Replicability

A

being able to repeat a study to check the validity of the results

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56
Q

Objectivity

A

observations made without bias

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57
Q

Falsification

A

that scientific statements are capable of being proven wrong

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58
Q

Inductive phase

A

observations yield information that is used to formulate theories as explanations

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59
Q

Deductive phase

A

Predictions made from theories, in the form of testable hypotheses, are tested and yield data that is analysed, leading to theory adjustment

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60
Q

Paradigm shifts

A

revolutionary changes in scientific assumptions

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61
Q

Predictive validity

A

predicting how well a test predicts future behaviour

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62
Q

Temporal validity

A

assesses to what degree research findings remain true over time

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63
Q

Field Experiment

A

An experiment that takes place in a natural setting where the researcher manipulates the IV and records the effect on the DV.

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64
Q

Advantages of a Field Experiment

A

+ More ecologically/externally valid

+ Fewer demand characteristics

+Replication can occur to some extent

+ Fewer experimenter effects

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65
Q

Disadvantages of a Field Experiment

A
  • Chance of extraneous variables
  • More time consuming
  • Ethical issues (informed consent)
  • Need a skilled researcher
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66
Q

Natural Experiment

A

An experiment where the change in the IV is not caused by the researcher as it would have happened if the researcher wasn’t there. The researcher records the effect on the DV.

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67
Q

Advantages of a Natural Experiment

A

+ No demand characteristics

+ No researcher effects

+ Fewer ethical issues

+ Allows P.ps who wouldn’t normally be tested to take part.

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68
Q

Disadvantages of a Natural Experiment

A
  • Lack of control (extraneous variables)
  • Short term behaviour may be displayed
  • No random allocation can create confounding variables
  • Harder to replicate
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69
Q

Quasi Experiment

A

The IV has not been determined by anyone the variables simply exist e.g. being old or young.

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70
Q

Extraneous Variables

A

Any variable apart from the IV which can effect the DV if not controlled. However they can be maintained or eliminated.

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71
Q

Confounding Variables

A

A variable apart from the IV which can effect the DV. However it can’t be controlled.

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72
Q

Control Condition

A

The IV isn’t changed and provides a baseline measure. the condition is in a repeated measures design that provides a baseline measure of behaviour.

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73
Q

Experimental Condition

A

Where you manipulate the IV. The condition is in a repeated measures design containing the IV as distinct from control.

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74
Q

Baseline Measure

A

Result established from control condition when no manipulation of IV occurs. Allows comparisons to be made.

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75
Q

Random Allocation

A

People are chosen randomly e.g. names from a hat meaning there’s an equal chance of being selected.

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76
Q

Ecological Validity

A

How methods can be applied to real life settings.

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77
Q

External Validity

A

How valid results are outside of a research setting.

78
Q

Demand Characteristics

A

Any cue from the researcher or research situation that can be interpreted by participants as revealing the purpose of the investigation leading them to changing their behaviour.

79
Q

Experimenter Effects

A

Where the experimenter changes a persons views usually sub-consciously through body language.

80
Q

Experimental Methods

A

The type of experiment you do.

81
Q

Experimental Designs

A

How you carry the experiment out.

82
Q

Independent Groups Design

A

Each participant either does the control condition OR the experimental condition.

83
Q

Advantages of Independent Groups Design

A

+ Reduces demand characteristics

+ Quick to administer

+ Could be used for all tests

+ Prevents order effects

84
Q

Disadvantages of Independent Groups Design

A
  • Individual differences can occur
  • Lots of P.ps are required
  • More time consuming
85
Q

Repeated Measures Design

A

Each participant does the control condition AND the experimental condition.

86
Q

Advantages of Repeated Measures Design

A

+ Quick to administer

+ No individual differences

+Fewer P.ps are required

87
Q

Disadvantages of Repeated Measures Design

A
  • High possibility of demand characteristics
  • Order effects can occur
  • Can’t be used for all tests
88
Q

Matched Pairs Design

A

Participants are matched on key characteristics. One participant does control condition and the other does the experimental condition.

89
Q

Advantages of Matched Pairs Design

A

+ Less possibility of demand characteristics

+ Prevents order effects

+ No individual differences

90
Q

Disadvantages of Matched Pairs Design

A
  • Time consuming
  • Lots of P.ps are required
  • Hard to match P.ps on all variables
  • Can’t be used for all tests
  • Not very economical
91
Q

Counterbalancing

A

An attempt to control order effects in a repeated measures design e.g. ABBA where when group does the experimental condition first where as the other does the control condition.

92
Q

Order Effects

A

A confounding variable arising from the order which participants take place in the different conditions e.g. boredom.

93
Q

Naturalistic Observation

A

Take place in a setting where behaviour would usually occur.

94
Q

Advantages & Disadvantages of Naturalistic Observations

A

+ High external validity

+ Easy to apply in everyday life

  • Hard to replicate
  • Extraneous variables can occur
95
Q

Controlled Observation

A

Some control over variables takes place to observe how people may interact/behave. They take place inside and outside of a lab.

96
Q

Advantages & Disadvantages of Controlled Observations

A

+ Easy to replicate

+ Less Extraneous Variables

  • Findings can’t be applied to all real life settings
97
Q

Participant Observation

A

The researcher is involved in/with the experiment. The researcher joins the group either overtly of covertly.

98
Q

Advantages & Disadvantages Participant Observations

A

+ Experience the same situation which gives insight which increases validity

  • Can get too attached to people and lose objectivity
99
Q

Non-Participant Observation

A

The researcher is not involved in what is going on. The researcher is external to what is going on/the people being observed.

100
Q

Advantages & Disadvantages of Non-Participant Observations

A

+ Allows researcher to maintain an objective psychological distance from P.ps

  • Researcher has less insight
101
Q

Covert Observation

A

Where the researchers status is not made clear to the group and the researcher doesn’t get consent.

102
Q

Advantages & Disadvantages of Covert Observations

A

+ No participant reactivity

+ Natural Behaviour - Increases validity

  • Ethics - People might not want to be observed`
103
Q

Overt Observation

A

The researcher is open about their intentions and seeks consent. People know they are being observed.

104
Q

Advantages & Disadvantages of Overt Observations

A

+ More ethically acceptable (have consent)

  • Can be influenced as they know they’re being watched
105
Q

Structured Observations

A

Key influence of the design of an observation is how the data is recorded.

Unstructured- Everything is written down; produces qualitative data

Structured - Only specifics are recorded; produces quantitative data

106
Q

Behavioural Observations

A

To produce a structured record of what the researcher hears or sees. The target behaviour is broken into behavioural categories that are observable and measurable. All target behaviour is included.

107
Q

Sampling Methods

A

Event Sampling - Counting the time a particular behaviour occurs in a group/individual.

Time Sampling - Recording behaviour with a pre established time frame.

108
Q

Inter-Observer Reliability

A

Two or more researchers observe the same behaviour at the same time then compare and amend results to create correlations.

109
Q

Correlational analysis advantages

A
  • allows predictions to be made
  • allows quantification of relationships
  • no manipulation
110
Q

Correlational analysis disadvantages

A
  • quantification problem
  • cause and effect
  • extraneous relationships
  • only works for linear relationships
111
Q

Content Analysis

A

a method of quantifying qualitative data through the use of coding units

112
Q

Strengths of content analysis

A
  • ease of application
  • complements other methods
  • reliability
113
Q

Weaknesses of content analysis

A
  • descriptive
  • flawed results
  • lack of causality
114
Q

Target Population

A

The entire group a researcher is interested in. The researchers wishes to draw conclusions from only the people in the group.

115
Q

Bias - sampling

A

When certain groups are over or under represented with in the sample selected. It limits the extent to which generalisations can be made to the target population.

116
Q

Generalisation

A

The extent to which findings and conclusions from a particular experiment can be broadly applied to the population. This is possible if the sample of people is representative of the population.

117
Q

The test-retest method

A

measures external reliability, by giving the same test to the same participants on two occasions

118
Q

External reliability

A

concerns the extent to which a test measures consistently over time

119
Q

Internal reliability

A

concerns the extent to which something is consistent within itself

120
Q

The split-half method

A

measures internal reliability by splitting the test into two and having the same participant do both halves

121
Q

Peer Review

A

The assessment of work by others who are specialists in the same field to ensure that any research set for publication is high quality.

122
Q

How is psychological research published?

A

Initially in journals which will then be translated into textbook information or be discussed at conferences,.

123
Q

Aims of Peer Review

A

1) To allocate funding properly and appropriately. It stops researchers spending lots of money on investigations which may encounter problems. Also it helps to develop the areas of psychology that need to be developed,
2) To validate the quality of research. It establishes more accurate to inter-observer reliability. Additionally it makes sure that you are measuring what you set out to measure.
3) To suggest amendments and improvements. It allows researchers to get more accurate results as it eliminates potential problems.

124
Q

Evaluation of Peer Review

A

+ Helps to establish validity and accuracy of research because more than one person will carry out the experiment therefore allowing the data to be correlated.

  • The anonymity could lead to them being overcritical . Changing data which is right and doesn’t need to be changed could give inaccurate results and may not be objective as they should be
  • Publication Bias can occur where only positive results or attention grabbing results are published. By publishing data which doesn’t support a hypothesis, it allows it to have more understanding and knowledge.
125
Q

Case Study

A

A research method that involves a detailed study of a signal individual, institution or event.

126
Q

Sampling Techniques

A

The method used to select people from the population.

127
Q

Opportunity Sampling

A

A sample of participants produced by selecting people who are most easily available at the time of the study.

128
Q

Opportunity sampling advantages

A
  • ease of formation

- natural experiments

129
Q

Opportunity sampling disadvantages

A
  • unrepresentative

- self selection

130
Q

Random Sampling

A

A sample of participants produced by using a random technique so that every member of the target population has an equal chance of being selected.

131
Q

Random Sampling advantages

A
  • unbiased selection

- generalisation

132
Q

Random sampling disadvantages

A
  • impractical

- not representative

133
Q

Volunteer Sampling

A

A sample of participants produced by a sampling technique that relies solely on inviting people to take part.

134
Q

Volunteer sampling advantages

A
  • ease of formation

- less chance of screw u phenomenon

135
Q

Volunteer sampling disadvantages

A
  • unrepresentative

- demand characteristics

136
Q

Systematic Sampling

A

Involves taking every nth person from a list to create a sample

137
Q

Systematic sampling advantages

A
  • unbiased selection

- generalisation

138
Q

Measures of Dispersion

A

The general term for any measure of the spread or variation in a set of scores.

139
Q

Descriptive Statistics

A

The use of graphs tables and summary statistics to identify trends and analyse sets of data.

140
Q

Pilot Study

A

A small scale trial carried out at the start of an experiment to check for any flaws e.g. do the questions in the questionnaire make sense.

141
Q

Mean

A

The arithmetic average. Calculated by adding up all of the values in a set of data and dividing by the number of values.

142
Q

Evaluation of The Mean

A

+ Most sensitive of the measures of central tendency as it includes all data

+ More representative

  • Easily distorted with extreme values therefore won’t be representative
143
Q

Median

A

The central value in a set of data when it is ordered from lowest to highest value.

144
Q

Evaluation of The Median

A

+ Extreme scores don’t have an effect

+ Easy to calculate

  • Not very sensitive as not all scores are included
145
Q

Mode

A

The value that appears most frequently in a set of data

146
Q

Evaluation of The Mode

A

+ Very easy to calculate

+ For data in categories it’s the only appropriate measure

  • Crude measure as the mean and mode can be very different
  • Not representative
147
Q

What measure of central tendency to use

A

Mean - If there are NO extreme values (most sensitive)

Median - If there are extreme values (the mean would be distorted)

Mode - Only if the data is in catogries

148
Q

Thematic analysis

A

a method of qualitative research linked to content analysis, which involves analyzing data to identify the patterns within it

149
Q

Thematic analysis stages

A
  1. familiarisation with the data
  2. coding
  3. search for themes
  4. reviewing themes
  5. defining and naming themes
  6. writing up
150
Q

Range

A

Calculation of the dispersion in a set of scores. Worked out by minusing the lowest value from the highest value and adding one as a mathematical correction.

151
Q

Evaluation of The Range

A

+ Easy to calculate

  • Only uses the 2 most extreme scores which may be unrepresentative of all the data
  • May not give a fair representation of the general spread of scores
152
Q

Standard Deviation

A

How far scores deviate from the mean

153
Q

Evaluation of Standard Deviation

A

+ More precise than the range as it includes all values with in the final calculation

  • Can be easily distorted by an extreme value e.g. the mean
154
Q

Types of graphs

A

Bar Chart

Scattergram

Histogram

Line graph

155
Q

What to include on a graph

A

Title showing a relationship between the co-variables

Labelled X and Y axis

Accurately plotted data

156
Q

Bar Charts

A

Used when data is divided into categories (discrete data)

The bars are separated to show different categories

157
Q

Histograms

A

Used when data is continuous

The bars touch each other

158
Q

Line Graphs

A

Represent continuous data

Each point is connected by a line

Usually the IV is plotted on the X axis and the DV is plotted on the Y axis

159
Q

Normal Distribution

A

There is a symmetrical spread of frequency data that forms a bell shaped pattern

160
Q

Characteristics of a normal distribution

A

Its bell shaped

Its symmetrical

The mean, median, mode are all in the centre

The 2 tails never touch the horizontal axis

161
Q

Positively Skewed Distribution

Right Skewed

A

The long tail is on the positive side of the peak and most of the distribution is centred to the left.

162
Q

Negatively Skewed Distribution

Left Skewed

A

The long tail is on the negative side of the peak and most of the distribution is concentrated on the right.

163
Q

Skewed Distributions

A

When the spread of data is not symmetrical meaning the data clusters to one end.

The mode is located at the highest point, then the median and finally the mean.

164
Q

Statistical Testing

A

We need to know if the results are significant i.e. are the results strong enough to reject the null hypothesis and accept the research hypothesis.

The difference may be due to chance or coincidence.

165
Q

The sign test

A

Involves counting up the number of positive snd negative signs.

To use the sign test we need to:

be looking for differences not associations

have used a repeated measures design

have data which is organised into categories (nominal)

166
Q

Accepted level of probability

A

In psychology the accepted level is 0.05 / 5%

Sometime researchers need more confidence so have a more stringent significance level of 0.01 / 1% e.g. when humans lives are involved.

167
Q

Calculated Value

A

The number the researcher is left with after the statistical test has been calculated. It is compared to the critical value to see whether the results are significant.

168
Q

Critical Value

A

The critical values table is given to you.

To use the critical values you need to know:

1) Desired significance level (usually 0.05)
2) The number (N) of participants
3) Whether the hypothesis is directional or non-directional

169
Q

Significant Results

A

The results are significant if the calculated value is equal to or lower than the critical value.

170
Q

How to carry out the sign test

A

1) Convert data into nominal data by subtracting one condition away from the other. If the number is negative you put a - sign and if it is positive you put a + sign in the sign of difference column
2) Add up the number of + & - signs (if p.ps got the same score in both conditions their data is ignored)
3) Take the less frequent sign and call this ‘S’ which id the calculated value
4) Compare the calculated value to the critical value (the calculated value needs to be equal to or less than the critical value).
5) Write up the sign test

171
Q

What to include in the sign test write up

A

The relationship between the calculated and critical value

How many participants there were

The significance level

Whether it was one tailed or two tailed

If its significant or not.

172
Q

Systematic sampling disadvantage

A
  • periodic traits

- not representative

173
Q

Stratified sampling advantages

A
  • representative

- unbiased

174
Q

Stratified sampling disadvantages

A
  • knowledge of population characteristics required

- time consuming

175
Q

Pie charts

A

Used to show the frequency of categories as percentages

176
Q

Stratified Sampling

A

A sampling technique where groups of participants are selected in proportion to their frequency in the population in order to obtain a representative sample.

177
Q

Confidentiality/anonymity

A

Participants data should not be disclosed to anyone unless agreed in advance

178
Q

Correlation

A

A mathematical technique, where a researcher investigates an association between two variables call co-variables.

179
Q

Positive Correlation

A

As one variable increase the other variable increases.

180
Q

Negative Correlation

A

as one variable increases, the other decreases

181
Q

Co-Variables

A

The variables investigated within a correlation e.g. height a weight.

182
Q

Zero Correlation

A

When there is no relationship between the co-variables.

183
Q

Statement for the sign test?

A

Used when we are looking for a Difference, using

Related measures design ( repeated or matched pairs) with Nominal

level data.

184
Q

Statement for Chi Squared?

+ solution

A

Justification - Used when we are look for a Difference, using

Independent measures design with Nominal level data.

calc the df + 1 tailed/ 2 tailed

185
Q

Statement for the Mann Whitney U test?

+ solution

A

Used when we are looking for a difference using independent measures when we have at least ordinal level data.

Na and Nb

186
Q

Statement for the Wilcoxon T test?

+ solution

A

Wilcox T test is used when you are

looking for a difference using a repeated measures or

matched pairs ( related measures) design with data

that is at least ordinal.

N p/pants + 1/2 tailed

187
Q

Statement for Related T test?

+ solution

A

Used when looking for a difference, using a related

measures design with data of interval level data which is parametric.

N -1 = df

188
Q

Statement for Unrelated T test?

+ solution

A

Used when looking for a difference, using a unrelated

measures design with data of interval level data.

Na + Nb -2 (un) =df

189
Q

How do you write a reference?

A

Author A. A. (Year). Title of the article. Name of the Periodical, volume(issue), #-#, link

190
Q

Statement for Pearson’s R?

+solution

A

Use Pearson’s R when you have a correlations study

which has interval level data that is Parametric.

N + 1/2 tailed tests

191
Q

Statement Spearman’s Rho?

+solution

A

Use a Spearman’s Rho when you have a correlations study which has

at least ordinal level data.

N + 1/2 tailed test

AQA Psychology (5 decks)

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