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Research Methods
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Cards (100)
Aim
A general expression of what the researcher intends to investigate
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Hypothesis
A precise and operationalised statement about the
assumed
relationship between variables
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Directional Hypothesis
States the
direction
of the predicted
difference
between two conditions or two groups of participants
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Non-directional
Hypothesis
Predicts simply that there is a
difference
between two conditions or two groups of participants without stating the
direction
of the difference
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Independent
Variable
Some event that either
naturally
varies or is directly manipulated by an experiment in order to test it's
effect
on another variable
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Dependent Variable
A
measurable
outcome of the action of the
independent
variable in an experiment
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Operationalise
Ensuring
that variables are in a form that can be easily
measured.
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Experimental method
A researcher causes the independent variable to vary and records the effect of the
IV
on the dependent variable. The
DV
must be operationalised.
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Control
(Refers to) The extent to which any variable is held
constant
or regulated by a
researcher
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Extraneous Variables
'Nuisance'
variables that do not vary systematically with the
IV.
A researcher may control some of these.
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Confounding
Variable
Change systematically with the
IV
so we cannot be sure if any observed change in the DV is due to the CV or the
IV.
CVs must be controlled.
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Demand Characteristics
Refers to any
cue
from the researcher or research situation that may reveal the
aim
of the study
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Investigator Effect
Any effect of the investigator's behaviour on the outcome of the research (the
DV
)
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Randomisation
The use of
chance
when designing investigations to control for the effects of
bias
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Standardisation
Using exactly the same
formalised procedures
for all ps in a research study
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Control groups
Control groups are used for the purpose of setting a
comparison.
They act as a 'baseline' and help establish
causation.
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Single Blind Design
A ps doesn't know the
aims
of the study so that
demand characteristics
are reduced.
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Double Blind Design
Both ps and researcher don't know the aims of the study to
reduce demand characteristics
and
investigator effects.
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Participant Variables
Individual differences. Differences among participants, overcome by a large sample size which dilutes any
extremes
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Situational Variables
People act differently in different situations. Time of day,
Lab
setting vs
Natural
setting
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Validity
(Refers to) Whether an
observed
effect is a
genuine
one
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External Validity
The degree to which a research finding can be
generalised
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Ecological
Validity
A type of
External
Validity - generalising to other settings
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Population
Validity
A type of
External
Validity -
generalising
to other groups of people
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Temporal
Validity
A type of
External
Validity - generalising to other times/over time
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Cultural
Validity
A type of
External
Validity -
generalising
to other cultures
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Internal Validity
The degree to which an observed effect was due to the experimental manipulation rather than other factors such as
extraneous
or
confounding
variables
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Mundane Realism
(Refers to) How a study mirrors the
real world.
The research environment is realistic to the degree to which experiences encountered in the research environment will occur in the
real world.
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Independent Groups
One group does one condition the other group does the other condition. Each ps experiences one condition and they're
randomly
allocated to the groups.
✔️no
order
effects
✔️no
demand characteristics
✖️more ps
✖️ps
variables
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Repeated Measures
Participants doing both conditions. To avoid order effects conditions should be
counterbalanced. AB-BA
✔️less ps
✔️no ps variables
✖️order
effects
✖️demand
characteristics
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Matched Pairs
Individuals matched up by characteristic (eg by IQ) and separated with one
half
of the pair in each group to overcome
individual differences
✔️less ps variables
✔️no order effects
✖️more ps
✖️matching is not
perfect
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Laboratory
Experiment
conducted in a lab, a
highly
controlled environment
✔️ highly controlled
evs
and
dvs
✔️ can be easily
replicated
✖️hard to
generalise
✖️demand
characteristics
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Field Experiment
A
natural
setting.
The researcher can control the
IV.
✔️Higher
external
validity
✔️No
demand
characteristics bc ps don't know they are taking part in a study
✖️Difficult to control
CVs
✖️Ethical
issues bc ps don't know they are taking part in a study
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Natural Experiment
IV cannot be manipulated because it
naturally exists
DV
naturally occurring
✔️an
ethical option
✔️high
external validity
✖️natural events occur
rarely
✖️ps are not
randomly
allocated so there is a
chance
of ps variables
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Quasi-Experiment
The IV is based on existing differences (eg
age
or
gender
) so can't be controlled
DV
naturally occurring
✔️High control
✔️Comparisons can be made btwn
ppl
(eg ppl with and without
autism
)
✖️Ps are not
randomly
allocated so
chance
of ps variables
✖️Causal
relationships not demonstrated
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Population
The
large
group of ppl that a
researcher
is interested in studying
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Sample
It is usually not possible to include all members of the population in the
study
, so a smaller group is selected - the
sample.
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Generalisation
The sample that is drawn should be
representative
of the population so
generalisations
can be made
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Bias
The majority of samples are biased in that certain groups may be
over
or
under-represented
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Opportunity Sample
Recruit people who are most
convenient
or most
available
(eg people walking by you in the street or students at school)
✔️Easiest method (use the
first
suitable participants you find).
✔️Less time to locate your
samples
✖️Inevitably
biased
(sample drawn from small part of population)
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