Chapter 6 Research Methods - Data analysis Flashcards
Qualitative data?
Written, non-numerical description of pts thoughts, feelings etc.
Quantitative data?
Expressed numerically rather than words.
Evaluation of qualitative data?
S - Rich in detail. Greater external validity.
L - Difficult to analyse. May be subjective.
Evaluation of quantitative data?
S - Easy to analyse (e.g. graphs). Less biased.
L - Narrower in meaning.
Primary data?
Collected firsthand for purpose of investigation.
Secondary data?
Collected by someone over than researcher.
Evaluation of primary data?
S - Fits the job, targets relevant information.
L - Requires time.
Evaluation of secondary data?
S - Inexpensive & easy to access.
L - Variation in the quality (e.g. outdated).
Meta-analysis - uses secondary data.
- Statistical analysis of large number of studies.
- Produces effect size.
Evaluation of meta-analysis?
S - Large sample, high validity.
L - Publication bias/file drawer problem.
Evaluation of the mean?
S - Most sensitive & representative.
L - Easily distorted by extreme values.
Evaluation of the median?
Less affected by extremes but not sensitive.
Evaluation of the mode?
S - Relevant to categorical data.
L - Crude, unrepresentative.
Standard deviation?
How much scores (on average) deviate from mean.
Evaluation of the range?
S - Easy to calculate.
L - Unrepresentative if there are extremes.
Evaluation of standard deviation?
S - More precise than range.
L - Distorted by extreme values.
Bar charts?
- Discrete categortical data.
- Frequency = height of bar.
Histograms?
Continuous data rather than discrete, so no space between bars.
Normal distribution?
- Bell curve.
- Mean, median & mode at same point.
- Tails never touch zero.
Skewed distributions?
- Negative leans right.
- Positive leans left.
