6.18 types of data💚

quantitative - data in the forms of numbers, objective. This is described in descriptive statistics which are then displayed on tables and graphs

Qualitative - data in the forms of words. Content analysis can turn qualitative into quantitative, or use categories and make a tally

When to use…

• Quantitative = experimental and observational research

• Qualitative = case studies, open ended interviews, questionnaires

• Can combine both to increase credibility = methodological triangulation

Evaluation

Quantitative

• objective, increasing scientific credibility

• Descriptive statistics allow data to be displayed on graphs, charts and tables

• More reliable

• Results lack depth and detail

Qualitative

• very detailed, higher validity

• May be biased/ open to interpretation

• Hard to summarise

• Lower reliability

Primary data - the researcher collects ‘first hand’ data. E.g experiments, observations, interviews, questionnaires and case studies

Secondary data - researcher uses information that’s previously collected by a third party. E.g statistic, records, published diaries or studies

Evaluation

Primary

• high validity, its specific to what’s being researched

• High validity, researcher can ensure theres control

• Time consuming

• Expensive

Secondary

• Quick and cheap

• Decreased validity, not specific to what’s being researched

• Decreased validity, cant ensue there was control

Meta analysis - collecting and combining the results of a range of previously published studies.

Evaluation

• large sample size, reliable

• Removes effects of bias or lack of control

• Can test the same variable in various contexts (e.g across cultures)

• Secondary data so no control over the data collected

• File drawer problem - studies that show a significant result are more likely to be be published, ignoring those that aren’t significant

• The choice of studies may be biased