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key terms Flashcards

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1
Q

Experimental design.

A

= Which participants are taking part in which conditions.

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2
Q

Repeated measures design.

A

= Participants do all conditions of the experiment, there results are compared to their own.

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3
Q

Independent groups design.

A

= Participants only complete one condition of the experiment and are compared to someone different in the other conditions.

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4
Q

Order effects

A

= The order in which the participant completes the conditions affects the results in repeated measures design.

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5
Q

Matched pairs design.

A

= participants only complete one condition of the experiment but are compared to someone similar to them.

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6
Q

Counterbalancing.

A

Aims to reduce the impact of order effects in repeated measures design by getting participants to complete the conditions in a different order (ABBA).

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7
Q

Random allocation.

A

The researcher randomly assigns participants to the conditions of the experiment.

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8
Q

Quasi experiment.

A

An experiment with no random allocation.

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9
Q

Extraneous variables.

A

Anything other than the IV that can affect the DV which should be controlled.

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10
Q

Operationalising.

A

Making variables and behaviours measurable.

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11
Q

Event sampling.

A

Noting every time a behaviour on the checklist occurs during an observation.

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12
Q

Internal validity.

A

The extent to which the experiment is testing what is supposed to.

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13
Q

Time sampling.

A

Noting a behaviour on the checklist which occurs in a given time frame.

Example = every 3O secs.

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14
Q

External validity.

A

The extent in which the results can be applied beyond the study.

  • Historical/temporal validity.
  • Ecological validity.
  • Cultural validity.
  • Population validity.
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15
Q

Independent variable.

A

The variable you change.

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16
Q

Dependant variable.

A

The variable you measure.

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17
Q

Directional hypothesis.

A

Predicts the direction of the results in an experiment or correlation.

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18
Q

Non-directional hypothesis.

A

Makes a prediction but does not state the direction of the results in an experiment or correlation.

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19
Q

Demand characteristics.

A

Participants changing their behaviour as they believe they know the aim of the study.

  • Please u effect
  • Screw u effect
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20
Q

Inter-observer reliability.

A

How similar the observers findings are to each other. It ain’t great unless in O.8.

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21
Q

Social desirability.

A

Participants changing their behaviour to suit perceived society norms or expectations

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22
Q

Researcher bias.

A

How the researcher influences the results.

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23
Q

Single blind technique.

A

The participant doesn’t know which condition they are in.

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24
Q

Double blind technique.

A

The participant and the experimenter does not know which condition the participant is in.

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25
Standardised instructions.
All participants given the same instructions, usually written.
26
Self-report.
Participants report on their behaviour. For example, questionnaire, interview.
27
Behavioural categories.
The operationalised behaviour looked for in an observation.
28
Quantitative data.
Numerical data.
29
Structured interview.
Interviewers have a list of questions to ask the participant, all participants are asked the same questions.
30
Unstructured interview.
Interviewers have a topic to ask the participant about, but it is more of a conversation.
31
Opportunity sampling.
Asking people who are available at the time to participate in the research.
32
Generalisable.
To what extent the research represents the target population.
33
Target population.
The people the researcher wants to generalise their results to.
34
Stratified sampling.
Choosing participants to equally represent the strata's (groups) of society.
35
Population validity.
The extent to which the sample used in the study represents the target population.
36
Temporal validity.
The extent in which the research can be applied over time.
37
Test-retest method.
Carrying out the test again and comparing the results to check the reliability. It aint great unless it's O.8.
38
Debrief.
Given to all participants at the end of the research to tell them what the research was about, thank them for taking part and reminding them of their right to withdraw.
39
Qualitative data.
Data in words.
40
Meta-analysis.
A analysis of the results of a collection of studies into the same area, to draw conclusions.
41
Descriptive statistics.
A way to describe trends in the data including measures of central tendency, measures of dispersion and graphs.
42
Statistical test.
Used to assess the significance of the results to be able to make inferences.
43
Critical value.
The value you need to compare your observed value to in order to determine whether your results are significant.
44
Observed/calculated value.
The value calculated from carrying out the statistical test.
45
Level of significance.
The level of how sure you are that your results are not down to chance. For example, O.O5.
45
Level of measurement.
The type of data collected from a study, nominal/ordinal/interval.
46
Nominal data.
Data that shows how many people fall into a category.
47
Ordinal data.
Data that can be ranked/put in order without fixed points between units. Subjective.
48
Interval data.
Data that can be put in order, with fixed units and equal distances between points on the scale. Objective.
49
Chi-square.
A statistical test to analyse nominal data, with repeated measures design, looking for a difference or correlation.
50
Sign test.
A statistical test to analyse nominal data, with repeated measures design, looking for a difference or correlation.
51
Mann-Whitney U
A statistical test to analyse ordinal data, with independent groups design, looking for a difference.
52
Wilcoxon test.
A statistical test to analyse ordinal data, with repeated measures design, looking for a difference.
53
Spearman's Rho test.
A statistical test to analyse correlational data which is ordinal.
54
Unrelated T test
A statistical test to analyse interval data, with independent groups design, looking for a difference.
55
Related T test
A statistical test to analyse interval data, with repeated measures design, looking for a difference.
56
Pearson's test.
A statistical test to analyse correlational data which is interval.
57
Publication bias.
Publishers only publish significant data, giving an unrepresentative understanding of the topic.
58
Significant.
The results are unlikely to be down to chance.
59
Content analysis.
Analysing communication by identifying the themes that occur, turning qualitative data into quantitative data, to then use statistical analysis.
60
Thematic analysis.
Analysing communication by identifying the themes that occur.
61
Concurrent validity.
The extent to which your results match that of an existing recognised measure of behaviour. It ain't great unless it's O.8.
62
Abstract.
A summary of the study at the start of the report, including the aims, hypotheses procedure, findings and discussion.
63
Appendix.
At the end of the report, including all the material and workings out, allowing the research to be replicated.
64
Type 2 error.
Using a probability too small, so you accepted the null hypothesis when you should have rejected it. You have been 2 strict.
65
Inferential statistics.
A test to assess the significance of your results, so you can make inferences.
66
Type 1 error.
Using a probability too big, so you rejected the null hypothesis when you should have rejected it. You think you are number 1.

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