Data and Analysis Flashcards
1
Q
nominal data
A
recording data in totals of named catagories
2
Q
ordinal data
A
recording data as points along a scale where the gaps between the points are not necessarily the same
3
Q
interval data
A
recording data as points on a scale where all gaps are equal
4
Q
quantitative data
A
numerical data
5
Q
strengths of quantitative data
A
- tends to be collected using objective measures
- collection tends to be highly reliable
- can be analysed using stats tests
6
Q
weaknesses of quantitative data
A
- doesn’t tell us why, reducing validity
7
Q
qualitative data
A
descriptive data
8
Q
strengths of qualitative data
A
- 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
9
Q
weaknesses of qualitative data
A
- 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
10
Q
measures of central tendency
A
- mode
- mean
- median
11
Q
measures of dispersion
A
- variance
- range
- standard deviation
12
Q
significance level
A
- the probability the pattern in the results could be due to chance
- p<0.05, reject the null hypothesis or accept the alternate hypothesis
13
Q
representativeness
A
- the extent to which a sample is representative of a population so the results can be generalised to the population
14
Q
generalisability
A
extent to which the findings can be applied to another sample/situation
15
Q
reliability
A
consistency of a measure