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Summary AS and A level Psychology Research Methods

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Compiled and Summarised notes all based on the Research methods used in Psychology

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  • Research methods
  • June 10, 2023
  • 7
  • 2022/2023
  • Summary
  • Secondary school
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Psychology - Research Methods Raida

Assumptions of approaches:
> Biological:
 Behaviours, emotions and cognitions can be explained via the brain and
hormones
 Behaviours can be explained via the brain, for example, the hippocampus is
involved in memory

> Cognitive:
 Behaviours and emotions can be explained in terms of the role of cognitive
processes like attention, memory and language
 Similarities and differences between people can be understood via cognitions.
These can be the way we process information

> Learning:
 Stimulus-response can help explain behaviour. In classical conditioning a dog
may salivate at the sound of a bell being rung
 Conditioning can help explain behaviour. A child may imitate the aggressive
behaviour they view from a model

> Social:
 Behaviours, emotions and cognitions can be influenced by other people, for
example in Milgram’s study, the participants obeyed the authority figure’s
orders as he appeared in a lab coat
 Behaviours, emotions and cognitions can be influenced by groups, for
example in an emergency situation, people might see other people calling for
help and just go on by when they usually help (ex. Pililavin et al)


 IV (independent variable): the variable manipulated by the researcher to
check its effect on the dependent variable
 DV (dependent variable): the variable being measured by the researcher and
is influenced by the independent variable
 Counterbalancing: dividing participants into two groups and have each
perform a slightly different task to cancel out the imbalance in the task
 Order effects: is how the positioning of the tasks influences the outcome

Experiments:
 Experiments look for a causal relationship in which Independent variable is
manipulated to influence a change in the dependent variable

> Types of experiments:
1. Laboratory experiment: conducted in an unnatural and collected
environment. IV is manipulated
2. Field experiment: conducted in a natural setting. IV is manipulated

, 3. Natural experiment: conducted in a natural setting, however, the IV isn’t
directly manipulated by the researcher, it happens naturally by chance
4. Quasi experiment: researcher has lots of control over the procedure, but not
over the allocation of participants (to groups)

> Strengths and Weaknesses:
1. Laboratory:
(strengths)
 Control over extraneous variables
 Causal relationship can be determined
 Standardised procedures increases reliability and replicability
(weaknesses)
 Lack of ecological validity (mundane realism)
 Participants could show Demand characteristics and Social desirability bias
2. Field:
(strengths)
 High ecological validity (as they’re showing their natural behaviour)
 Less likely to show demand characteristics and social desirability bias
(weaknesses)
 Low control over extraneous variables reduces reliability and replicability
 Can’t be sure dependent variable is due to the independent variable or other
(confounding) variables
 Participants are unaware of their participation; ethical issue of informed
consent
3. Natural:
(strengths)
 High ecological validity
 Less likely to show demand characteristics and social desirability bias
 Researchers can study variables that would usually be unethical/impractical
to study
(weaknesses)
 Only possible when IV naturally occurs
 Controlling extraneous variables are difficult
 Causal relationships are difficult to establish
 Hard to replicate as levels of standardisation is difficult to achieve. Low
reliability as well

> Experimental designs: is how participants are allocated to the conditions of the
study
1. Independent measure design: different groups of participants are used for
each level of the IV
2. Repeated measure design: each participant takes part in every condition of
the study
3. Matched pairs design: participants are matched in pairs according to a
characteristic they have that is similar

> Strengths and Weaknesses:
1. Independent measure design:

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