Types of data Flashcards
Qualitative data
Non-numerical data expressed in words e.g. extract from a diary.
What is a strength of qualitative data?
Richness of detail.
Much broader in scope than quantitative data.
More meaningful, greater external validity.
What is a limitation of qualitative data?
Difficult to analyse.
Hard to identify patterns and make comparisons.
Leeds to subjective interpretation and researcher bias.
Quantitative data
Numerical data e.g. reaction time or number of mistakes
What is a strength of quantitative data?
Easier to analyse.
Can draw graphs and calculate averages.
So comparisons between groups can be made.
What is a limitation of quantitative data?
Narrower in meaning.
Expresses less detail than qualitative data.
Lower external validity - may be less like real life.
Primary data
First hand data collected for the purpose of the investigation.
What is a strength of primary data?
Fits the job.
Study designed to extract only the data needed.
Information is directly relevant to research aims.
What is a limitation of primary data?
Requires time and effort.
Designing and collating questionnaires takes time and expense.
Secondary data can be accessed within minutes.
Secondary data
Collected by someone other than the person who is conducting the research e.g. work of other psychologists or government statistics.
What is a strength of secondary data?
Inexpensive.
The desired information may already exist.
Requires minimal effort making it inexpensive.
What is a limitation of secondary data?
Quality may be poor.
Information may be outdated or incomplete.
Challenges the validity of any conclusions.
Meta-analysis
A type of secondary data that involves combining data from a large number of studies. Calculation of effect sizes.
What is a strength of meta-analysis?
Increases validity of conclusions.
The eventual sample size is much larger than individual samples.
Increases the extent to which generalisations can be made.
What is a limitation of meta-analysis?
Publication bias.
Researchers may not select all relevant studies, leaving out negative or non-significant results.
Therefore conclusions may lack validity.
