research methods and statistics Flashcards
what are the two categories self-report can be split into?
interview and questionnaire
what is self-report research method?
asking paticipants about topic personally for their own report
self-report strengths
researchers can obtain participant’s beliefs, emotions and experiences that they could not observe. high validity, more representative of behaviour being measured
self-report weaknesses
social desirability bias so pps could lie to give researchers what the pps think they want, lacks validity. data often not generalisable so not representative of full population, not reliable
structured interview
pre-set q’s with fixed responses-high reliability but q’s might not be asked in the same way causing lack of consistency
semi-structured interview
pre set q’s but no fixed responses- high reliability but open to interpreter bias
unstructured interview
no fixed questions or answers- high validity but open to social desirability bias
questionnaires
often contains several items to draw information from pps
pilot study
small-scale preliminary version of study, primary of questionnaires
pilot study reasons
check question clarity, check sample method for representativity, check questions are universally understandable, no leading questions, check questions aren’t upsetting to pps, ensure format has enough room
open-ended questions
invite pps to describe and explain providing qualitative data
closed questions
provide pps with a limited choice of answers to collect quantitative data
likert scales
pps given a scale of several options and must pick the option they agree with most, not just a rating scale but still quantitative data but not reliable as numbers can be interpreted differently
rating scales
allow pps to express preferences using numbers but not reliable as numbers can be interpreted differently
experiments
manipulation of variables to create ways to measure factors affecting behaviours
laboratory experiment
-manipulated iv and measured dv
-controlled variables
-artificial enviro/task
-allocation of pps to groups
field experiment
-manipulated iv and measured dv
-controlled variables
-natural enviro/task
-allocation of pps to groups
natural experiment
-natural iv and measured dv
-no control of variables
-natural enviro/task
-no allocation of pps to groups
quasi experiment
-natural iv and measured dv
-controlled variables
-artificial enviro/task
-no allocation of pps to groups
independent measures
variable being manipulated
dependent measures
variable being measured for results
operationalising variables
defining in very specific terms the variables being tested so that the iv is definitely the cause of the effect (dv)
independent measures design
pps only take part in one condition of the experiment
repeated measures design
pps take part in all conditions
factors affecting repeated measures design
task order interferes with pps performance due to practice from previous tasks or fatigue
correlation
measures relationship between variables
positive correlation
as one variable increases, so does the other
negative correlation
as one variable increases, the other decreases
zero correlation
no relationship between variables
example one-tailed hypothesis
there will be significantly more of variable a observed than variable b
example two-tailed hypothesis
there will be a significant relationship between variable a and variable b
example null hypothesis
there will be no significant relationship between variable a and variable b and any relationships observed with be up to chance
strengths of correlation
-can be used in place of experimental manipulation that would otherwise be unethical or impossible
-when only one variable is known, the other variable score can be predicted
weaknesses of correlation
-cannot predict cause and effect
-relationship may be affected by extraneous variables
observation
process of watching and recording pps behaviours
overt observations
pps know they are being watched
covert observations
pps don’t know they are being observed during the research
participant observation
researcher is involved and participating in the research
non-participant observation
researcher is not part of activity or group or behaviour being observed
structured observation
some variables controlled by the researcher and usually carried out in lab conditions
naturalistic observation
pps watched in their natural environment and behaviour recorded as it happens without manipulation
observation behaviour sampling techniques
researcher must decide intervals at which behaviours will be recorded and what specific behaviours will be recorded which can yield qual and quant data
observation time sampling
recording set behaviour at set time intervals
observation event sampling
recording every instance of specific behaviour every time it happens rather than at specified instances
content analysis
allows analyzing of written communication such as lengthy texts which can be broken down into manageable units of data so it can be converted into qualitative or quantitative data
content analysis strengths
reductionist as it converts complex text into numbers and standardised so more reliable
content analysis weaknesses
open to researcher bias so they might only utilise data that aligns with hypothesis and qualitative data can be interpreted differently
case study
studies singular pps or small groups looking at unique characteristics and behaviours
case study strengths
allow in depth investigation and triangulation of various data forms and allow unique, one-off situations so pps can be better protected from harm
case study weaknesses
only generalisable to specific individuals and often effected by desirability bias
longitudinal research
investigation of the same group of pps behaviours on numerous occasions over an extended period of time
longitudinal research strengths
ind diff removed as confounding variable is measured so high validity. good way of showing how ind behaviours develop over time
longitudinal research weaknesses
pps often drop out of the research over time making data less consistent. open to interpreter bias as relationships can form over the long periods
cross sectional research
collection of a variety of types of pps at a single moment in time to compare development amongst different ppl. often used to assess cultural or background
cross sectional research strengths
take into account a wide range of diff pps at one moment in time so high pop val. easier to control variables due to being carried out in a single moment in time so more valid
cross sectional research weaknesses
affected by ind diff in the diff groups of ppl. difficult to replicate due to wide range of pps so low reliability
meta analysis
a review of secondary data, not a study itself
meta analysis strengths
allows many different sources to be used so more holistic. does not create ethical issues so doesn’t harm pps because there are none directly
meta analysis weaknesses
open to researcher bias as they could just only use the studies that support their hypothesis. no direct control over how previous research was conducted
