A01:
VARIABLES: A01:
AIMS AND HYPOTHESIS: A01:
EXPERIMENTAL DESIGN:
Independent variable – the thing you change, Aim – statement of what is wanting to be found Independent groups – participants perform in
with multiple conditions (‘to see if’) one condition, multiple groups
Dependant variable – the thing you measure Hypothesis – a prediction of the findings, Reduces order effects (such as effects of
containing both conditions of the IV and an practice, fatigue, boredom)
Extraneous variable – something other than
operationalised DV
the IV that effects the DV Reduces demand characteristics (such as
Null hypothesis – predicts that there will be no guessing the aim of the experiment)
Confounding variable – something that effects
hypothesis
the DV that cannot be controlled (e.g. effort) Increases participant variables (individual
Non - directional (two -tailed) – predicts there differences between participants). Requires
Operationalisation – make the variables
will be a difference more people
measurable so anyone could replicate
experiment Directional hypothesis – predicts what results Repeated measures – participants perform in
will be all conditions, one group
Reduces participant variables (as same person
does all conditions)
Increases order effects (boredom, practice etc)
Increases demand characteristics (guess the
aim)
Matched pairs – participants are matched with
someone with same important characteristics
for study, they perform in one condition each
Lowered participant variables
Reduces order effects/demand characteristics
Time consuming, expensive and difficult to
conduct
, A01:
SAMPLING: A01:
Stratified sampling (Quota) – based on A01:
Investigator effects – bias of person conducting
percentages in target population, e.g. if 10% of experiment, counteracted by a double blind
Target population – group of society that
population is French, 10% of sample should be
researcher wants to study Double blind – experimenter and participants
French
both unaware of the aim of the study, increases
Sample – section of target population to do
Representative of target population validity
experiment that’s representative of TP
Expensive and time consuming, so rarely used Peer review – where someone else also an
Opportunity sample – using whoever is
expert in the field, reads over
available and willing to take part
report/experiment and findings to check for
Quick and easy to obtain CONTROLS: validity. Done before it is published, checks if
research is correct, interesting, good
Might not be representative of TP Counterbalancing – reduces order effects in methodology, new and valid
repeated measures designs, by one condition
Experimenter bias, might chose people that will Makes sure only accurate true research is
doing A then B and others doing B then A
fit hypothesis (sometimes subconscious) published, advantage as it protects integrity of
Randomisation – used to avoid researcher bias, journal it is published in and good name of
Random sample – all TP have equal chance of
aka in process of splitting words into two lists, university and subject
being picked, participants are selected in a non-
pull out of a hat and put one in A one in B
bias way such as names in a hat Protect funding, as if untrue findings published
Random allocation – same principle ^ but for funding would be revoked
No experimenter bias as no control
people/participants
Might not be representative Time consuming to get published
Standardisation – making the method of
Difficult if sample is large experiment scientific and measurable so it can More likely to have peer review at more
be replicated, everything should be the same in prestigious universities
Systematic sample (Quasi-random) – every nth
each condition, reduces extraneous variables Can be held onto by other expert if they are
person is selected from alphabetical list until
you reach amount required Demand characteristics – the idea that wanting to delay publication as they are
participants could guess the aim of the study, working on own study
No experimenter bias
can be reduced by independent Tend to publish positive findings, which fit an
May not be representative, is time consuming groups/matched pairs design existing ‘status quo’
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