Component 2: definitions Flashcards

1
Q

Independent variable

A

The variable manipulated by the researcher to investigate whether it brings about a change in the dependent variable

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2
Q

Dependent variable

A

The variable the researcher measures but does not manipulate in an experiment

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3
Q

Operationalisation

A

The process of making variables measurable

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4
Q

Standardisation

A

A set of procedures or instructions that are kept the same

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5
Q

Random allocation

A

Allocating participants to experimental groups using random techniques

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6
Q

Experimental condition

A

Refers to the group of participants who are exposed to the independent variable

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7
Q

Control condition

A

Lacks any treatment or manipulation of the independent variable

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8
Q

Extraneous variable

A

Not measured or manipulated by the researcher, affects results of all participants equally, might impact the DV if not well controlled

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9
Q

Extraneous variable examples

A

Gender, age, temperature, noise volume, weather, location, experimenter

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10
Q

Confounding variable

A

Damages the results, anything the researcher is not aware of or cannot control

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11
Q

Confounding variable examples

A

Mood, amount of sleep, competitiveness, personality

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12
Q

Aim

A

A general statement describing the purpose of an investigation

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13
Q

Hypothesis

A

A testable statement that can be proven or disproven

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14
Q

Directional hypothesis

A

A testable statement based on previous research, findings predict the direction of results between conditions

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15
Q

Key terms: directional hypothesis

A

More/less, increase/decrease, higher/lower

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16
Q

Non-directional hypothesis

A

A testable statement with no previous research findings or conflicting research, predicts an effect not a direction

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17
Q

Key terms: non-directional hypothesis

A

Difference or effect

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18
Q

Null hypothesis

A

There is no difference or effect between the variables, any differences are due to chance factors

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19
Q

Locations of research

A

Laboratory, field, online

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20
Q

Lab location

A

Artificial environment, participants know they are being studied, maximum control of variables

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21
Q

Demand characteristics

A

Participants aware they are being studied, they change their behaviour as a result, it is unknown whether the behaviour they display is real or true

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22
Q

Field location

A

Less controlled than lab, natural environment, everyday location,

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23
Q

Online location

A

Faster to find larger, global group of participants

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24
Q

Mundane realism

A

The extent to which a study reflects a real life environment

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25
Q

Ecological validity

A

The extent to which findings of the study can be applied to the real world
(environment)

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26
Q

Types of experiment

A

Laboratory, field, natural, quasi

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27
Q

Quasi experiment

A

No deliberate manipulation of the IV, no random allocation of participants to experimental groups, IV is a naturally occurring difference, often an innate characteristic, DV measured in a lab

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28
Q

Lab experiment

A

Controlled and artificial setting, contains both experimental and control conditions, random allocation, IV and DV

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29
Q

Natural experiment

A

Research does not deliberately manipulate IV - it occurs naturally, DV is tested in a lab, field or online

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30
Q

Field experiment

A

Participants unaware they are being researched, IV and DV

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31
Q

Lab location: advantages and disadvantages

A

Control over extraneous and confounding variables, easier replication of research, high demand characteristics

32
Q

Field location: advantages and disadvantages

A

Lower demand characteristics = more natural behaviour, high ecological validity and mundane realism, difficult to control confounding and extraneous variables, lab equipment may be difficult to transport

33
Q

Online location: advantages and disadvantages

A

Access to a diverse and larger group of participants, cost effective and fast, methods are limited = surveys or questionnaires, ethical issues = consent and protection of participants

34
Q

Name the three types of experimental design

A

Independent measures, repeated measures, matched pairs

35
Q

Independent measures

A

Participants take part in only one condition

36
Q

How many groups of participants are there in a independent measures design?

A

Two seperate groups

37
Q

Repeated measures

A

Participants take part in all conditions of the experiment

38
Q

How many groups of participants are there in a repeated measures design?

A

One group

39
Q

Matched pairs

A

Participants are matched in each condition for their characteristics, may have an effect on their performance, each participant takes part in one condition

40
Q

How are participants matched in a matched pairs design?

A

One for one (in pairs), by having the same characteristic as their pair, but each participant takes part in one condition

41
Q

Name the three types of order effects

A

Practice, fatigue, boredom

42
Q

What are the advantages of an independent measures design?

A

No order effects, demand characteristics are less of a problem

43
Q

What are the disadvantages of an independent measures design?

A

Individual differences (participant variables) are an issue

44
Q

What are the advantages of a repeated measures design?

A

Eliminates participant variables

45
Q

What are the disadvantages of a repeated measures design?

A

Order effects may be present, greater chance of demand characteristics

46
Q

What are the advantages of a matched pairs design?

A

No order effects, controls participant variables (individual differences)

47
Q

What are the disadvantages of a matched pairs design?

A

Time consuming and difficult to get right

48
Q

How can individual differences in an independent measures design be controlled?

A

Random allocation

49
Q

How can order effects in a repeated measures design be controlled?

A

Counterbalancing

50
Q

What is counterbalancing?

A

ABBA: half of the group does condition one then two, the other half does condition two then one

51
Q

How can participant variables be further minimised in a matched pairs design?

A

Identical twins

52
Q

Name the seven sampling techniques

A

Opportunity, self-selected, random, systematic, stratified, quota, snowball

53
Q

What is the target population?

A

The larger group from which the sample is drawn

54
Q

What is a sampling frame?

A

A list of all members of the target population

55
Q

Describe opportunity sampling

A

People are chosen who are available at the time of study and fit the criteria

56
Q

Describe self-selected sampling

A

People put themselves forward for a study, respond to advert on social media

57
Q

Describe random sampling

A

Everyone has an equal chance of getting selected (e.g. random number generator), list of target population needed

58
Q

Describe systematic sampling

A

Every nth person is selected (fixed intervals), list of target population needed

59
Q

Describe stratified sampling

A

Random based, representitive of population = random selection and the sample represents the demographics of the population

60
Q

Describe quota sampling

A

Opportunity based, representitive of population = researcher chooses participants and gets set quota from each category of the population

61
Q

Describe snowball smapling

A

Initial contact used to provide further contacts, usually used when target population is not easy to accessd

62
Q

Strengths of opportunity sampling

A

Convenient + quick to carry out, economical

63
Q

Weaknesses of opportunity sampling

A

Biased (those chosen are those who look approachable), not representitive (similar kinds of people), selective (small group of target population

64
Q

Strengths of self-selected sampling

A

Ethical, not very time consuming (participants approach researcher)

65
Q

Weaknesses of self-selected sampling

A

Respondents are open to demand characteristics, not representitive (specific type of person)

66
Q

Strengths of random sampling

A

Sample selected in unbiased way (everyone has equal chance of getting selected)

67
Q

Weaknesses of random sampling

A

Time consuming to create list of people if large population, not neccessarily most representitive way, may select one type of person

68
Q

Strengths of systematic sampling

A

Unbiased as objective, quick to carry out once frame created

69
Q

Weaknesses of systematic sampling

A

Not everyone has equal chance of being included, not truly random or representitive

70
Q

Strengths of stratified sampling

A

Equal representation of all groups, everyone in each category has equal chance in being selected

71
Q

Weaknesses of stratified sampling

A

Difficult to identify sub-categories, requires organisation = time consuming

72
Q

Strengths of quota sampling

A

Equal representation of all groups, quicker as participants selected from each group conveniently (opportunity based)

73
Q

Weaknesses of quota sampling

A

Requires organisation = time consuming, may be biased as sample not random (opportunity based)

74
Q

Strengths of snowball sampling

A

No sampling frame required, may give access to groups difficult to access (e.g. deviant groups)

75
Q

Weaknesses of snowball sampling

A

Time consuming, not random = may not be representitive, may run out of new contacts

76
Q

Name the ethical issues

A

Privacy, Confidentiality, Deception, Right to withdraw, Informed consent, Protection from harm (PC DRIP)