Social Psychology - Experiments

Question 1

Research Methods in Social Psychology

◦ O[blank_start]bservation[blank_end]
◦ S[blank_start]urvey[blank_end]
◦ C[blank_start]orrelation[blank_end]
◦ E[blank_start]xperiments[blank_end] and [blank_start]Quasi[blank_end]-[blank_start]experiment[blank_end]

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bservation

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urvey

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orrelation

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xperiments

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Quasi

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experiment

Question 2

Observation - A type of study in which individuals are observed or certain outcomes are measured.

◦ No attempt is made to affect the [blank_start]outcome[blank_end] (for example, no treatment is given)
◦ You are simply a [blank_start]passive bystander[blank_end], watching behaviour as it unfolds

Varies in methodology:
[blank_start]Casual[blank_end] Observation
◦ ‘People watching’ to gain some sort idea of what is going on
◦ E.g. do parents coach their kids from side-lines at sports matches?

[blank_start]Systematic[blank_end] Observation – behaviour [blank_start]systematically[blank_end] observed & recorded
◦ What percentage of parents coach their kids at matches?
◦ What type of kids receive more coaching?
◦ What type of parents give more coaching?

Varies in setting:
◦ [blank_start]Naturalistic[blank_end] or not

Strengths:
◦ Allows analysis of behaviour in [blank_start]natural[blank_end] setting
◦ Lessens impact of [blank_start]artificial[blank_end] contextual/environmental effects
◦ Useful in [blank_start]early[blank_end] stages of research program

Weakness:
◦ Observations may be [blank_start]biased[blank_end]/not [blank_start]representative[blank_end]
◦ Complex [blank_start]environmental[blank_end] influences
◦ Little or no [blank_start]experimental[blank_end] control
◦ The degree to which the experimenter can [blank_start]reduce[blank_end] the influence of unwanted factors (e.g. extraneous and confounding variables)

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outcome

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passive bystander

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Casual

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Systematic

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systematically

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Naturalistic

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early

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natural

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artificial

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biased

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representative

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environmental

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experimental

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reduce

Question 3

Self-report data

[blank_start]Questionnaires[blank_end] completed to gauge personal preferences, beliefs, attitudes etc.
◦ How much time do you spend studying per day? Do you prefer X or Y? What is your favourite X?

Strengths:
◦ Easily [blank_start]administered[blank_end]
◦ Can recruit very large [blank_start]samples[blank_end] (representativeness)
◦ Can provide a lot of [blank_start]information[blank_end]
◦ Low [blank_start]subjectivity[blank_end] in interpretation

Weaknesses
◦ [blank_start]Self-report[blank_end] bias
◦ Content [blank_start]sensitivity[blank_end]
◦ Participant [blank_start]engagement[blank_end]
◦ Applicable to only to limited range of [blank_start]research[blank_end] topics

Accepted Answer

Questionnaires

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administered

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samples

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information

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subjectivity

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Self-report

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sensitivity

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engagement

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research

Question 4

Correlational Studies

Investigate the [blank_start]relationships[blank_end] between two or more [blank_start]variables[blank_end]
◦ Does income correlate with happiness?
◦ Does time spent in the library correlate with grades?
◦ Does IQ predict physical health?

[blank_start]Positive[blank_end] correlation (same)
◦ As you study more – grades increase

[blank_start]Negative[blank_end] correlation (inverse)
◦ As men live longer – less hair

No correlation
◦ No apparent relationships between variables (e.g. litres of orange juice consumed per day and number of shoes owned)

Strengths:
◦ Allows general [blank_start]predictions[blank_end]
◦ Can indicate a causal [blank_start]relationship[blank_end]
◦ Facilitates collection of larger [blank_start]datasets[blank_end] (compared to experimentation)
◦ Provides strong [blank_start]starting[blank_end] point for further experimentation

Weakness:
◦ Does not prove [blank_start]cause[blank_end] and effect
◦ Can not explain [blank_start]relationships[blank_end] (only identify their presence)
◦ Correlation may be [blank_start]spurious[blank_end]
◦ Correlations may be mediated by a [blank_start]confounding[blank_end] variable

Accepted Answer

variables

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relationships

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Positive

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Negative

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predictions

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relationship

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datasets

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starting

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cause

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relationships

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spurious

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confounding

Question 5

Experiment

An experiment is a scientific test which is done in order to discover what happens to something in particular [blank_start]conditions[blank_end]
- involves the [blank_start]manipulation[blank_end] of an [blank_start]independent[blank_end] variable and the [blank_start]measurement[blank_end] of its effect on a [blank_start]dependent[blank_end] variable
◦ E.g. Compare the Maths test grades of two group of students, one of which received study skills training while the other completed extra Math classes

- Compares the effect of different [blank_start]conditions[blank_end] (in which the [blank_start]independent[blank_end] variable is modified) on the [blank_start]dependent[blank_end] variable by [blank_start]comparing[blank_end] groups
◦ [blank_start]Experimental[blank_end] group - Group which receives a given intervention (e.g. Maths classes)
◦ [blank_start]Control[blank_end] group - Group which receives no intervention or an intervention not believed to have an effect ([blank_start]passive[blank_end] vs. [blank_start]active[blank_end] control)

Types of variables:
[blank_start]Independent[blank_end] (IV)
◦ the variable being manipulated (e.g. intervention type)

[blank_start]Dependent[blank_end] (DV)
◦ the variable of interest being measured (e.g. test grades)

[blank_start]Confounding[blank_end]
◦ a ‘hidden’ or ‘unknown’ variable which actually explains the relationship between the ind. and dep. variables

[blank_start]Extraneous[blank_end]
◦ other aspects of the environment that may influence results (e.g. time of testing, environment factors)

Accepted Answer

conditions

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manipulation

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independent

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measurement

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dependent

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conditions

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independent

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dependent

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comparing

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Experimental

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Control

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passive

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active

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Independent

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Dependent

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Confounding

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Extraneous

Question 6

Criteria for good experiment

[blank_start]Representative[blank_end] sample
◦ Always study the type of people who are relevant to your research question

Random [blank_start]selection[blank_end] & [blank_start]assignment[blank_end]
◦ Ensure groups are roughly equal on variables relevant to the study

Include [blank_start]control[blank_end] group

Avoid [blank_start]confounding[blank_end] variables

Avoid [blank_start]demand[blank_end] characteristics
◦ Sometimes, participants ‘give the experimenter what they think he/she wants

Avoid experimenter [blank_start]bias[blank_end]
◦ Data must be analysed objectively, without a ‘preferred’ result

Accepted Answer

Representative

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selection

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assignment

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control

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confounding

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demand

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bias

Question 7

Experiment Strengths & Weaknesses

Strengths:
◦ Allows [blank_start]experimental[blank_end] control
◦ Facilitates [blank_start]identification[blank_end] of cause & effect
◦ Can indicate a [blank_start]causal[blank_end] relationship
◦ Gives arguably the “[blank_start]richest[blank_end]” data

Weakness:
◦ Behaviour may be [blank_start]altered[blank_end] by experimental setting
◦ Results may not [blank_start]generalise[blank_end]
◦ Experimenter effects
    - [blank_start]Demand[blank_end] characteristics
    - Experimenter [blank_start]bias[blank_end]

Accepted Answer

experimental

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identification

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causal

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richest

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altered

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generalise

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Demand

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bias

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