different ways to analyse data, study's, etc Flashcards
meta analysis
-method of analysis data which produces an effect size
-examines data from a number of independent studies in the same subject to determine overall trends
effect size
quantitative measure of studies effect
case study
the detailed study of a single individual, institution or event using info from a range of sources e.g. family friends or person concerned
longitudinal (case studies)
follow group over extended amount of time
what observation is content analysis
indirect, observing the individual from the artifacts they produce e.g songs, books, paintings
meta analysis strengths
-reviewing from range of studies increases validity
-reduces contrast in studies by producing statistics
meta analysis weaknesses
-research designs in diff studies may vary meaning u cant truly compare them
-so arent always valid
case study strengths
-rich in depth data
-overlooked data likely to be identified
-used incases where experiments arent ethical e.g how respond to certain events
case study weaknesses
-difficult to generalise data
-as it is identified after the event we cannot be sure the apparent changed weren’t present originally
content analysis strengths
-based on what people actually do, real communications that are current and relevant
-high ecological validity
-when sources are obtained, findings can be replicated
content analysis weaknesses
- observer bias may reduce objectivity and validity of findings
-diff observers interpret the meaning of behavioural categories differently (e.g anger)
-lack internal validity
types of extraneous variables
demand characteristics, investigator effects, situational variables, participant variables
demand characteristics
if participant knows/guesses the experiment and changes their behaviour
investigator effects
any aspect of the researcher’s behaviour, appearance or gender that could affect participant responses
situational variables
features of a research situation that may influence participants behaviour e.g. order effects, heat, time of day
participant variables
differences between participants (e.g. IQ, age)
confounding variable (not extraneous)
variables that interfere with the effect of the IV and the DV
extraneous variable
variable that only effects the DV
content analysis
a method used to analyse qualitative data
benefits of content analysis
-high ecological validity
-high mundane realism
-analysis can be repeated so reliable
weakness of content analysis
-big culture bias and interpretation of verbal or written content affected by language and culture of observer
-observer bias- affects objectivity and validity
how to deal with validity in content analyses
researcher needs to ensure sample is representative
-use a double blind technique
how to deal with issues of reliability
-test retest (another researcher retests analysis)
-inter observer reliability (two or more observe same artefacts)
-training observers in use of coding system through practice
what average goes with nominal data
mode
