8. Data types Flashcards
(12 cards)
What is QN data?
- Numerical data usually using scores from ppt
- Aims to produce results easily comparable and analysed using graphs and stats tests
- Collected from questionnaires
What is QL data?
- Meaningful results from natural setting
- Aims to understand individual ppt POVs and understand experiences
- Concerns lang interpretation as well as thoughts and feelings
- Collected from case studies, unstructured observations + interviews
strengths of QN data
+ Easy to analyse: graphs can show comparisons between groups
+ Statistics more objective as less open to interpretation increasing reliability
+ High internal validity because data less subjective therefore higher chance IV DV C+E
weaknesses of QN data
- Lacks depth and detail of QL data
- Learn little about participant thoughts (less meaningful)
- Doesn’t tend to have same validity as Ql data as doesn’t reflex real world complexities
strengths of QL data
+ more depth and detail as ppt can fully express themselves giving more insight increasing validity
+ fully report thoughts, feelings, opinions
+ High external validity: real world insights
+ more meaningful
weaknesses of QL data
- Difficult analysis: researcher may have pages of interview transcript to filter through
- Conclusions and patterns drawn from researchers POV therefore subjectivity + open to bias
strengths of primary data
- suits aim of research as researchers knows what data needed for investigation
- authentic as from first hand ppts
- known data source increasing credibility
What is primary data?
- QL / QN
- collected first hadn’t by researcher using any research methods
- collected for specific aim
What is secondary data
Second hand data collected by another researcher meaning all exists before researcher does investigation
weaknesses of primary data
- Time consuming and costly as must design experiment and seek ppt
Strengths of secondary data
+ easy to access and less time consuming: time taken to collect data not needed
+ data alr checked: less time and effort
weaknesses of secondary data
- studies conducted may not fit with researcher’s aim
- may be out of date, incomplete or poor quality meaning time wasted
