Data and Analysis Flashcards
nominal data
recording data in totals of named catagories
ordinal data
recording data as points along a scale where the gaps between the points are not necessarily the same
interval data
recording data as points on a scale where all gaps are equal
quantitative data
numerical data
strengths of quantitative data
- tends to be collected using objective measures
- collection tends to be highly reliable
- can be analysed using stats tests
weaknesses of quantitative data
- doesn’t tell us why, reducing validity
qualitative data
descriptive data
strengths of qualitative data
- high levels of validity due to participants being able to express themselves more fully
- less likely that key or ‘rare’ observations are lost through averaging or simplifying the data
weaknesses of qualitative data
- collected using subjective measures
- collection may be invalid as recording or interpretation of responses may be biased by researcher’s opinions or feelings
- data are individual so can be difficult to generalise
- time consuming to analyse
measures of central tendency
- mode
- mean
- median
measures of dispersion
- variance
- range
- standard deviation
significance level
- the probability the pattern in the results could be due to chance
- p<0.05, reject the null hypothesis or accept the alternate hypothesis
representativeness
- the extent to which a sample is representative of a population so the results can be generalised to the population
generalisability
extent to which the findings can be applied to another sample/situation
reliability
consistency of a measure
internal reliability
The extent to which the results are
consistent across the same measure
external reliability
The extent to which a measure produces the same results in the same situation with the same people
inter-rater reliability
A method of measuring the consistency of a measure by assessing the measures of multiple different observers or “raters” to ensure similarities in how they record/rate data
Typically useful for observations
test-retest
testing reliability by using the same test twice and if the scores correlate well, then it has good reliability
validity
how accurate a piece of research or test is at what it aims to measure
internal validity
- the extent to which the procedures in a study achieve the intended manipulations and measures
- high internal validity means you can be sure the DV is a result of the IV
face validity
- the extent to which a study appears to do what it is supposed to - its effectiveness
construct validity
extent to which what is being measured actually exists
population validity
extent that findings from one sample can be generalised to to the whole target population
ecological validity
- extent that findings from one situation can be applied to another
- whether the study accurately measures real life
demand characteristics
cues or features of an experiment/situation that could indicate to the participant the aims of the study and influence their behaviour
social desireability
the tendency of participants to respond/act in a way they think reflects what is acceptable in society and not what they actually want to respond/behave
researcher bias
the tendency of researchers to act in ways that influence the results to reflect things such as their own beliefs or culture
observer bias
- tendency for observers to see what they want to see
- recording behaviours they believe should/will occur and not the behaviours that actually occur
researcher effects
negative influences researchers have on the study by their presence, beliefs, gender etc
observer effects
- overt observation
- presence, beliefs etc can influence the study
external validity
the extent to which the findings from a specific situation or study will generalise to other situations
