Research methods Flashcards
experimental designs
different ways in which testing participants can be organised in relation too experimental conditions
matched pairs
repeated measures
independent measures
matched pairs
each condition uses different but similar participants
repeated measures
all participants experience both conditions
independent measures
participants experience 1 level of the IV
2 separate groups experience 2 different conditions
strengths of independent measures
avoids order effects
weaknesses of independent measures
less economical
extraneous variables
strengths of repeated measures
more economical
less chance of extraneous variables
weaknesses of repeated measures
order effects
more chance of demand characteristics
strengths of matched pairs
less individual differences
avoids order effects
weaknesses of matched pairs
time consuming
still extraneous variables
levels of data
nominal
interval
ordinal
nominal levels of data
categorise/classification
time of the day-AM or PM
ordinal levels of data
ordinal scale indicates direction
time of the day-night, dawn, noon, afternoon, evening
interval levels of data
same distance between each variable
time of day-1,2,3,4,5
graph distribution
normal
right-skew
left-skew
normal distribution
the graph isn’t skewed
both sides are even
mean, median, mode are all in the middle of the graph
right-skew
positive skew
right side is longer
mode is to the left of median and mode
left-skew
negative skew
left side is longer
mode is to the right of mean and median
hypothesis
null
alternative
directional
non-directional
null hypothesis
result is due to chance
no relationship between variables
alternative hypothesis
a relationship between the variables
directional hypothesis
significant increase
significant decrease
states the difference between the 2 variables
non-directional hypothesis
significant difference
states there will be a difference between the 2 variables
type 1 errors
the link is mistaken
believe the null hypothesis isn’t true so reject it
false positive
in reality the null is true
type 2 erros
don’t think there is a link but there is
believe the null hypothesis is true
false negative
in reality the null isn’t true
values
find significant difference to accept/reject the null hypothesis
critical values
determines whether a result represents a real difference
value a test result must exceed to be considered to be significant
result compared to the critical value
observed value
observed value is compared to critical value
values found by conducting research
predictive validity
the extent to which findings can be used as an indication of future performance
concurrent validity
the extent to which a measure relates to an existing similar measure
face/content validity
where a measure is scrutinised to see whether it appears to measure what is it supposed to
historical/temporal validity
the extent to which findings can be generalised to other times/era
ecological validity
the extent to which findings can be generalised to other settings/situations
construct validity
the extent to which findings fit with theoretical knowledge
population validity
the extent to which findings can be generalised to other groups/individuals
internal validity
face/content
concurrent
construct
external validity
predictive
ecological
historical/temporal
population
internal reliability
the consistency of the measuring device
external reliability
the consistency of the measure device over time
assessing internal reliability
spilt half
assessing external reliability
test-retest method
features of a science
objectivity falsifiable paradigm replicability theory construction empirical method
feature of science
objectivity
information based on fact
features of a science
falsifiable
the principle that a theory can’t be considered scientific unless it admits the possibility of being proved untrue
features of a science
paradigm
set of shared assumptions and agreed methods within scientific discipline
features of a science
replicability
the extent to which scientific procedure can be repeated
extraneous variable
any other variable that isn’t the IV which can effect the DV if it isn’t controlled for
confounding variables
any variable other then the IV which may have affected the DV
randomisation
the use of chance in order to control for the effects of researcher bias
lab experiment
experiment that takes place in a controlled environment where the researcher manipulates the IV and records the effect on the DV
Field experiments
an experiment that takes place in a natural setting within which the researcher manipulates the IV and records the effect on the DV
natural experiment
an experiment where the change of the IV isn’t brought about by the researcher and would have occurred if the researcher wasn’t there
the research records this effect on the DV
Quasi-experiment
the IV hasn’t be determined by anyone the variables just exist
