qualititative and quantitative data are empirical data
qualitative
'quality'
written
expresses thoughts/feelings
cannot be quantified
eg interviews
quantitative
'quantity'
numerical
how much/how long/how many
measured
quantitative evaluation
:-) easy to analyse, quick and precise
:-( limited therefore lacks detail
qualitative evaluation
:-) can form further research, full scope of info
:-( difficult to analyse, researcher bias
primary data is gathered first hand by the researcher
primary data evaluation
:-) control over data, recent and current
:-( lengthy, time consuming and expensive
secondary data is collected by someone else
secondary data evaluation
:-) easy, cheap and quick
:-( past data may not be relevant, may not be exact
meta analysis is a statistical technique for combining findings of several studies
independent variable is the one you change
dependent variable is the one thats measured
extraneous variables are anything that isn't the IV effecting the DV, become confounding variables if uncontrolled
an aim is a clear and precise statement of the purpose of the study
a hypothesis is a testable statement predicting the results of the research. if the results support the hypothesis its retained. if it doesn't, it's rejected
non directional aka two tailed hypothesis
states the iv will have an effect on the dv but doesn't predict how
a non directional hypothesis should use the words significant difference
directional aka one tailed hypothesis
the iv will have an effect on the dv and what the effect is
directional hypotheses should include a direction word eg higher or lower
null hypotheses states there will be no significant effect of the iv on the dv
operationalisation is defining the variables so they can be tested precisely
the experimental methods are lab, quasi, field and natural
laboratory experimental method
setting: artificial
iv: manipulated
example: effects of alcohol on reaction time in a controlled setting
:-) replicable, high variable control to establish C+E
:-( low ecov, high dc's
quasi experimental method
setting: usually artificial
iv: naturally occuring eg sex
example: gender difference in time completing memory task
:-) replicable, high variable control to establish C+E
:-( low ecov, high dc's
field experimental method
setting: natural
iv: manipulated
example: piliavin
:-) high ecov, low dc's
:-( hard to replicate, low variable control
natural experimental method
setting: natural
iv: natural
example: smoking was banned from all public places for a six-month period
:-) high ecov, low dc's
:-( hard to replicate, low variable control
extraneous variables
participant variables, situational variables, experimenter effects and demand characteristics
demand characteristics are environmental clues and cues in an investigation that cause unnatural behaviour, to please the researcher, to skew the results for funny or self consciousness
to improveinternal validity, the researcher must control extraneous variables
Validity means accuracy; whether a study measures what it intends to measure
internal validity - does it measure what it intends to?
were ev's controlled?
external validity - can the research be generalised outside of the research setting to other settings (ecological), other people (population) or other times (temporal)
assessing validity
face validity - 'on the face of it'
concurrent validity - does it provide a closematch to results from established test
improving validity
experiments - high control, standardised procedures
questionnaires - anonymity
observations - covert
qualitative methods - triangulation (more than one research method)
reliability means consistency. the results are reliable if the same results are consistently found
just because a study is reliable it doesn't mean it's valid. a study can be reliably invalid