Involves notes on:
- Variables, Types of Experiments
- Control of Variables
- Observation and Self-Report Techniques
- Correlations, Aims, and Hypotheses
- Sampling, Design, and Data
- Ethics
- Probability and Significance
- Distributions
- Content Analysis
Involves strengths and weakness...
Variables, Types of Experiments:
● Variable: any ‘thing’ that can change within an investigation
○ Variables are generally used in experiments to determine if changes in one thing
results in changes in another
● Independent variable: the variable in the experimental situation that is manipulated
(changed) by the researcher (or it might change naturally) so the effect on the Dependent
Variable (DV) can be measured
● Dependent variable: The variable that is measured by the researcher
○ Any effect on the Dependent Variable (DV) should be caused by the change in the
Independent Variable (IV)
● Types of experiments
○ Lab
■ An experiment conducted in a tightly controlled environment where the IV is
manipulated at the researcher observes the effect of this on the DV
○ Field
■ An experiment carried out in a natural environment
■ The IV is still manipulated but it is done in an environment which is typical of
the behaviour being studied
○ Natural
■ Studies that take advantage of changes in the environment
■ The IV is not brought about by the researcher; it would have happened even
if the researcher was not there
○ Quasi
■ The IV is based on an existing difference between people (e.g. age or gender)
■ No one manipulates the IV, it just exists
● Strengths and weaknesses of lab experiments:
○ + High control over extraneous variables (the researcher can ensure that the change
in IV caused the effect on the DV). Therefore, the study demonstrates cause and
effect (high internal validity)
○ + Replication is more possible than in other types of experiments because of the high
level of control (ensures new extraneous variables are not introduced when
repeating an experiment)
■ This is important to check that the results are valid and not just a one-off
○ - May lack generalisability because the lab environment may be artificial and not like
everyday life (participants might behave in unusual ways)
■ This means their behaviour can’t be generalised beyond the research setting
(low external validity)
○ - Participants are usually aware they are being tested in a lab so they might behave
unnaturally (demand characteristics)
○ - The tasks participants carry out in a lab might not represent real-life experience
(low mundane realism)
● Strengths and weaknesses of field experiments
, ○ + Have higher mundane realism than lab experiments because the environment is
more natural
■ Therefore, field experiments might produce behaviour that is more valid and
authentic, especially as participants might not know they are being studied
(high external validity)
○ - Field experiments have less control over extraneous variables
■ This means cause and effect between the IV and DV is much harder to
establish and replication is often not possible
○ - There are also ethical issues
■ If participants do not know they are being studied, they cannot give their
consent and so the research might invade their privacy
● Strengths and weaknesses of natural experiments
○ + Allows research to take place that might not be ethical otherwise
○ + Natural experiments often have high external validity because they involve the
study of real-life issues and problems as they happen
○ - A naturally occurring event might happen very rarely, reducing the opportunities
for research
■ This also means that there is less scope for generalising findings to other
situations
○ - Participants might not be randomly allocated to experimental conditions, which
means the researcher might be less sure that the IV affects the DV
● Strengths and weaknesses of quasi-experiments
○ + Quasi-experiments are often carried out under controlled conditions and therefore
share the same strengths as a lab experiment
○ - Quasi-experiments, like natural experiments, cannot randomly allocate participants
to experimental conditions, and therefore there might be confounding variables
● To minimise the effects of extraneous or confounding variables, different steps can be taken
by the researcher like randomisation and standardisation
○ Randomisation: the use of chance to reduce the effects of bias from investigator
effects
■ This can be done for the design of materials, deciding the order of
conditions, the selection of participants, etc
○ Standardisation: using the exact same formalised procedures and instructions for
every single participant involved in the research process
■ This allows for elimination of non-standardised instructions as being possible
extraneous variables
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