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A-LEVEL PSYCH > RESEARCH METHODS > Flashcards

RESEARCH METHODS Flashcards

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1
Q

Define aim

A

What researcher intends to investigate

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2
Q

Define hypothesis

A

Clear, precise and testable statement that states the relationship between variables being investigated

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3
Q

Define variable

A

Factor that can be changed in an investigation

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4
Q

Define independent variable

A

Experimental situation that researcher manipulated or it changes naturally

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5
Q

Define dependent variable

A

Measured by the researcher to see how it changed

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6
Q

Define operationalisation

A

Turning abstract concepts from your aim into clearly define variables that can be measured

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7
Q

Define directional hypothesis

A

Kind of difference/relationship between IV and DV(one-tailored hypothesis)

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8
Q

Define non-directional hypothesis

A

Predicts that there will be a difference between conditions but can’t predict which direction it’ll go (two-tailored hypothesis)

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9
Q

How do researchers decide what type of hypothesis to use

A

One tailed if previous research suggests an outcome.
Two tailed if no previous research or it’s inconclusive

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10
Q

Define extraneous variables

A

Any variable other than the IV that may have an effect on the DV (if it is not controlled).

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11
Q

Define confounding variables

A
  • Do systematically change with the IV.
  • Any variable other than the IV that may have affected the DV so we cannot be sure of the true reason for the DV changing.

e.g. personality

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12
Q

Define investigator effects

A
  • Any effect of the researcher’s behaviour that could change the outcome of the results (DV).

e.g. smiling more when lying

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13
Q

How can extraneous variables and confounding variables be controlled?

A
  • Standardisation > All participants should be subject to the same experimental condition (i.e. environment, time etc).

Randomisation > Using chance in order to control for the effects of bias in an experiment.

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14
Q

Define participant and population

A
  • Participant-people who take part in the research
  • Population-group of people from whom the sample is drawn
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15
Q

Why does sample must be representative

A

in order to generalise your findings from your sample to the population

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16
Q

Whats random sampling

A
  • Every member of the target population has an equal chance to be chosen

1) Compile a list of all target population
2) Assign each name and number
3) Select a sample using random number generator

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17
Q

Advantages of random sampling

A
  • No researcher bias
  • Increased internal validity > confounding & extraneous variable distributed between two groups.
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18
Q

Disadvantages of random sampling

A
  • Difficult to get a complete list of target population
  • Time consuming
  • Participants may refuse to take part
  • May randomly draw a non-representative sample
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19
Q

What’s systematic sampling

A
  • Every nth member of the target population is selected

1) Create a list of the target population in order (sampling frame)
2) Take sample from list

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20
Q

Advantages of systematic sampling

A
  • Objectives > avoids researcher bias > researcher has no influence once the sample is chosen
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21
Q

Disadvantages of systematic sampling

A
  • Could still draw a non-representative sample
  • Time consuming > costly
  • Participants may refuse to take part
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22
Q

What’s stratified sampling

A
  • Composition of the sample reflects proportions of certain subgroups in the target population

1) Identify different subgroups in the population
2) Work out proportion of each group
3) Participants in each subgroup are selected randomly in the same proportion as the target population

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23
Q

Advantages of stratified sampling

A
  • Avoids researcher bias
  • More representative of the whole population > findings are more generalised
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24
Q

Disadvantages of stratified sampling

A
  • Stratification is never perfect > complete representation of population is not possible
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25
Q

What’s opportunity sampling

A

Sample from people who are available and willing when the study is carried out (e.g. psychology undergraduates).

1) Select whoever is available at the time.
No need to obtain a list of the target population.
No need to devise a method of random selection - saves time.

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26
Q

Advantages of opportunity sampling

A
  • Quick
  • Convenient
  • Less costly
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27
Q

Disadvantages of opportunity sampling

A
  • Unrepresentative of the target population > cannot generalise
  • Researcher controls selection so may avoid certain people > researcher bias.
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28
Q

What’s volunteer sampling

A

Self-selected sampling – participants become part of the study when asked or in response to an advert.

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29
Q

Advantages of volunteer sampling

A
  • Convenient.
  • Less time consuming.
  • No researcher bias.
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30
Q

Disadvantages of volunteer sampling

A
  • Often unrepresentative. Volunteers may have similar profile (e.g. people with spare time) > volunteer bias.
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31
Q

Define experimental design

A

How you allocated your participant to the different conditions in an experiment

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32
Q

List the 3 experimental designs

A
  • Independent group
  • Repeated measures
  • Matched pairs
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33
Q

What’s independent group

A
  • Participants take part in 1 condition
    -Required a separate group for each condition then results for each group, usually by comparing mean results
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34
Q

Advantages of independent groups

A
  • Avoids order effects > reduces boredom and fatigue
  • Reduces demands characteristics
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35
Q

Disadvantages of indepedent groups

A
  • Needs lots of participants > costly
    -Difference between groups (participant variables) > may affect result; however random allocations can overcome this
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36
Q

Define order effects

A

When the order of the conditions in an experiment has an effect on participant behaviour.

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37
Q

What’s repeated measures

A
  • Participants do all conditions
  • Results compared at the end
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38
Q

Advantages of repeated measures

A
  • Avoids participants variables as everyone does all the conditions
  • Fewer people needed > less costly
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39
Q

Disadvantages of repeated measures

A
  • Order effects more likely > requires counterbalancing
  • Demand characteristics more likely as participants are more likely to guess the aim.
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40
Q

Define counterbalancing

A

Alternating the order in which participants take part in different conditions.

e.g. 1) control followed by experiment
2) experiment followed by control

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41
Q

Define matched pairs

A
  • Participants are matched in each condition for any characteristics that may affect performance. E.g. age, gender, IQ.
  • Results are compared between members of each pair.
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42
Q

Advantages of matched pairs

A

-Reduces participant variables
- Reduces order effects and demand characteristics

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43
Q

Disadvantages of matched pairs

A
  • Very time-consuming > costly
  • Impossible to match pairs exactly (even for twins) > may be unexpected confounding variables.
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44
Q

Confounding variable

A

A kind of extraneous variable that systematically change with the IV.
Any variable other than the IV that may have affected the DV so we cannot be sure of the reason for the DV changing.

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45
Q

Participant variable

A

any individual differences between participants that may affect DV

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46
Q

Situational variables

A

any features of the experimental situation that may affect DV

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47
Q

Examples of participant variables

A

Personality, age, gender, motivation

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48
Q

Examples of situational variables

A

weather, instructions, temperature, time of day, noise

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49
Q

Demand characteristics

A

Any cue from the researcher or from the research situation that may be interpreted by participants as revealing the purpose of an investigation. This leads to a participant changing their behaviour within the research situation

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50
Q

How can we control extraneous and confounding variables ?

A

1) standardisation- All participants should be subject to the same experimental conditions
2)Randomisation- Using chance in order to control for the effects of bias in an experiment

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51
Q

Order effects

A

When the order of the conditions in an experiment has an effect on particular behaviour

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52
Q

counterbalancing

A

Alternating the order in which participants take part in different conditions

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53
Q

What is an experiment ?

A

There is an IV sometimes manipulated by the researcher
The effects of the IV on the DV are observed or measured so that the hypothesis can be tested
The participants are allocated randomly to the conditions, where possible.

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54
Q

lab experiments strengths

A

control extraneous variables- increases objectivity + validity
- can be standardised, easy to replicate

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55
Q

Lab experiments limitations

A

Artificial conditions-low ecological validity, demand characteristics, experimenter bias, low mundane realism, ethics

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56
Q

difference between field and natural experiment

A

natural also takes place in a real life setting but unlike field, researcher has no control over either the environment or variables so iv is therefore likely to be naturally occuring

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57
Q

Field experiment strengths

A

greater ecological validity, more mundane realism, behaviour more valid, fewer demand characteristics

58
Q

Field experiment limitation

A

Less control- more possible extraneous variables, harder to replicate, ethics

59
Q

Natural experiments strengths

A

High ecological validity, can research areas that would make experiments impossible for ethical reasons

60
Q

natural experiments limitations

A

Very difficult to replicate, fewer opportunities for research, little control over extraneous variables

61
Q

Quasi experiments

A

Not true experiment
IV based on existing differences between people (E.g., age, gender)
studies that are almost experiments. The IV doesn’t vary- its a set condition that exists.

62
Q

advantage of quasi experiment

A

Carried out in controlled environment – shares strengths of lab experiments

63
Q

disadvantage of quasi experiment

A

Cannot randomly allocate participants to a condition, like natural experiment - may be confounding variables.

64
Q

Lab Experiment

A

an experiment carried out in a controlled setting.Participants know they are being studied

65
Q

Field Experiment

A

an experiment conducted outside of the lab but the IV is still manipulated. Participants usually unaware that they are being studied.

66
Q

Natural Experiment

A

an experiment in which the experimenter has not manipulated the independent variable directly.

67
Q

pilot studies

A

-a small scale trial run of a study, completed before the actual research
-can check methodology to highlight what isn’t working
-you can then change things without it affecting your actual study
-results of the pilot study are irrelevant

68
Q

why do people use pilot studies?

A

-check if the IV is manipulated correctly
-check if the measure of the DV is correct
-check if the measure is appropriate and if people understand it
-avoid wasting time and money

69
Q

BPS

A

British Psychological Societ

70
Q

Deception

A

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

71
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.

72
Q

Protection from harm

A

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

73
Q

Debrief

A

Researchers should discuss the aims of the research with the participants making sure they know how they’ve contributed to meeting the aims

74
Q

Privacy

A

Participants’ right to privacy must be maintained.
We should only observe people where they would expect to be observed by others in public places.

75
Q

Confidentiality

A

information about our participants is protected by the Data Protection Act.
Participants must not be identifiable in published research.
Participants are given numbers or referred to by code or their initials.

76
Q

Dealing With Informed Consent

A

-Participants issued with a consent letter or form detailing all relevant information that might affect their decision to participate.
-If under 16 parents need to sign

77
Q

What if getting consent would ruin your study…?

A

-Presumptive consent
-Prior general consent
-Retrospective consent

78
Q

Single Blind Procedure

A

-Participant does not know which experimental condition they are in.
-Limits demand characteristics

79
Q

Double Blind Procedure

A

-Participant and researcher do not know which experimental condition the participant is exposed to (another researcher oversees the investigation).
-Limits demand characteristics and removes researcher bias

80
Q

Observational Techniques:Naturalistic

A

-Watching/recording behaviour in the setting where it would normally take place.
-All aspects of the environment are free to vary.

81
Q

evaluation of naturalistic

A

+More external validity.
+Findings can be generalised to real life.
-Replication is difficult

82
Q

Observational Techniques:Controlled

A

-Watching/recording behaviour within a structured environment where variables are managed.
-Control over variables and also extraneous variables.

83
Q

evaluation of controlled

A

+Replication easy due to control
-Lacks ecological validity
-Cannot be generalised to real-life situation

84
Q

Observational Techniques:Covert

A

-Participants’ behaviour is watched and recorded without their knowledge or consent.

85
Q

evaluation of covert

A

+Removed participant reactivity
+Increased validity
-Ethical Issues

86
Q

Observational Techniques:Overt

A

-Participants’ behaviour is watched and recorded with their knowledge or consent.

87
Q

evaluation of overt

A

+Ethically acceptable
-Could increase participant reactivity.

88
Q

Observational Techniques:Participant

A

-Researcher becomes a member of the group whose behaviour they are observing

89
Q

evaluation of participant

A

+Researchers experience the whole situation – gives them insight.
-Lose objectivity

90
Q

Observational Techniques:Non-participant

A

Researcher remains outside of the group whose behaviour they are observing.

91
Q

evaluation of non participant

A

+Maintain objective in observations
-May lose insight due to being ‘on the outside.’

92
Q

Recording Observations:Unstructured

A

Write down everything the observer sees.
Provides rich detail… often too much.

93
Q

evaluation of unstructured

A

-Produce qualitative data, more difficult to record and analyse.
+richer data
-higher risk of observer bias.

94
Q

Recording Observations:Structured

A

Target behaviours for a main focus.
Allows the researcher to quantify their observations using a pre-determined list of behaviours and sampling methods.

95
Q

evaluation of structured

A

+Use of behavioural categories make the recording easier and more systematic.
+Data more likely to be numerical - analysis is more straightforward.

96
Q

Sampling Methods:Event sampling +evaluation

A

counting the number of times a particular behaviour occurs.
-Useful when the target behaviour or event happens quite infrequently and could be missed if time sampling was used.

97
Q

sampling methods:time sampling +evaluation

A

recording behaviour with a pre-established time frame.
-Effective in reducing the number of observations that have to be made.

98
Q

what are Questionnaires

A

-Set of written questions used to assess a person’s thoughts and/or experiences.
-May be used to assess the DV

99
Q

what are open questions ?

A

-Provide qualitative data- hard to analyse but provides rich data.
-Allow people to give opinions and feelings.

100
Q

what are closed questions?

A

-Fixed choice (yes/no, tick boxes)
-Provides quantitative data- easy to analyse.

101
Q

strengths of questionnaires

A

+Cost effective
+Large amounts of data
+Easy to distribute to large numbers of people
+Easy to analyse data (normally)

102
Q

weaknesses of questionnaires

A

-Demand characteristics
-Response biases

103
Q

different type of questionnaire designs

A

-Likert
-rating
-fixed questions

104
Q

interviews: structured

A

Pre-determined questions asked in a fixed order.

105
Q

interviews:semi-structured

A

Likely to experience in everyday
life, list of questions that have been decided but also free to expand (job interview)

106
Q

interviews: unstructured

A

Works like a conversation, no set questions, interviewee encouraged to expand on questions.

107
Q

evaluation of structured interviews

A

+easy to replicate due to standardised format
+reduces differences between interviewers
-not possible to debate topic

108
Q

evaluation of unstructured interviews

A

+gives more insight due to flexibility
-analysis of data is hard (qualitative)
-social desirability
-drawing conclusions may be difficult

109
Q

what does a correlation illustrate?

A

strengths and direction of association between two or more co-variables.

110
Q

Positive Correlation

A

As one co-variable increases, the other co-variable also increases.

111
Q

Negative Correlation

A

As one co-variable increases, the other co-variable decreases.

112
Q

Testing the strength of a correlation

A

calculate a correlation coefficient to show how strong the association is between two co-variables.

113
Q

what does a correlation co efficient do?

A

enables us to see the direction of the correlation and how strong the correlation is.

114
Q

what are the strengths of correlations?

A

+Useful as a preliminary tool to assess the strength of a relationship.
+May suggest ideas for later research
+Quick and economical to carry out

115
Q

what are the weaknesses of correlations?

A

-Cannot demonstrate cause and effect
-Third variable problem (intervening variable)
-Can be misinterpreted or misused to peoples advantage

116
Q

Meta analysis

A

The process of combining the findings from a number of studies on a particular topic. The aim is to produce an overall statistical conclusion (the effect size) based on a range of studies. A meta-analysis should not be confused with a review where a number of studies are compared and discussed

117
Q

The difference between correlation and experiments

A

In an experiment the researcher controls or manipulates the independent variable
(IV) in order to measure the effect on the dependent variable

In contrast, in a correlation, there is no such manipulation of one variable and therefore it is not possible to establish cause and effect between one co-variable and another.

118
Q

Bar chart

A

-results in categories
- also called discrete data or discontinuous data

119
Q

Histogram

A

Used when the data is continuous in the form of intervals

120
Q

Scattergrams

A

used to show the relationship between 2 co-variables
- each point usually represents 1 participant

121
Q

Line graph

A

used to show a trend

122
Q

descriptive statistics

A

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

123
Q

Measures of central tendency

A

General term for any measure of the average value in a set of data.

124
Q

Mean

A

The arithmetic average calculated by adding up all the valued and dividing by how many there are
+ includes all data (representative)
- can become easily distorted by extreme values

125
Q

Median

A

The central value in a set of data when values are arranged lowest to highest.
+extreme values don’t affect it, easy to calculate
- less representative

126
Q

Mode

A

The most frequently occurring value in a set of data.
+ easy to calculate
- not representative

127
Q

Measures of dispersion

A

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

128
Q

Range

A

Simple calculation of the dispersion in a set of scores which is worked out by subtracting the lowest score from the highest and adding 1 as a mathematic correction
+ easy to calculate
- only take into account extreme values

129
Q

Standard deviation

A

Sophisticated measure of dispersion in a set of scores. It tells us by how much on average each score deviated from the mean
+ precise
- distorted by a single extreme value

130
Q

small standard deviation

A

scores cluster around the mean

131
Q

large standard deviation

A

scores are spread out from the mean

132
Q

Normal distribution

A

A symmetrical spread of frequency data that forms on a bell shaped pattern

133
Q

Skewed distribution

A

A spread of frequency data that is not symmetrical, where the data clusters to one end

134
Q

positive skew

A

The opposite to a positive skew

135
Q

Probability

A

Probability refers the likelihood that the results in a study occurred by chance. The accepted level of probability level used in psychology is 0.05 = 5%
P< 0.05
This means there is less than or equal to, 5% probability the results occurred by chance, or to put it another way we can be 95% certain the results are due to manipulating the independent variable.
The researcher can be pretty certain the difference found was because of the independent variable not just chance.

136
Q

Requirements for a Sign test

A

-a difference in our data sets (not a correlation)
-repeated measure design in our experiment (we assign each participant with a +, - or = depending on how their performance has changed or not).
-data that is organised into categories (nominal data)

137
Q

Peer Review

A

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

138
Q

What is peer review used for

A

Validate quality and relevance of research
Suggest amendments or improvements
Allocate research funding
(e.g. by Medical Research Council)

139
Q

problems with the Peer Review Process

A

Anonymity
Reviewers may use anonymity to negatively affect other researchers (their competitors).
Publication Bias
Journals may prefer to publish ‘headline’ research to increase readership of their journal.
Also tend to favour research with positive results.
Maintaining the Status Quo
Reviewers are usually established researchers.
May be less likely to pass innovative research (especially if it contradicts their own research!).
This may slow down the progress of research.

140
Q

Define ‘economy’

A

The state of a country or region in terms of the production and consumption of goods and services.

141
Q

The implications of psychological research for the economy”

A

How does psychological research affect, benefit or devalue financial prosperity?

142
Q

Treatment of mental health disorders

A

Absence from work estimated to cost £15 billion per year.
1/3 related to mental health (anxiety, depression, stress).
Effective treatment allows patients to manage their conditions and return to work.

A-LEVEL PSYCH (17 decks)

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