7/19 Using software for statistical analysis
Some key concepts
Before we look at types of analysis and tools we need to be familiar with a few concepts first:
- Population - the whole units of analysis that might be investigated, this could be students, cats, house prices etc
- Sample - the actual set of units selected for investigation and who participate in the research
- Variable - characteristics of the units/participants
- Value - the score/label/value of a variable, not the frequency of occurrence. For example, if age is a characteristic of a participant then the value label would be the actual age, eg. 21, 22, 25, 30, 18, not how many participants are 21, 22, 25, 30, 18.
- Case/subject - the individual unit/participant of the study/research.
Sampling
Sampling is complex and can be done in many ways dependent on 1) what you want to achieve from your research, 2) practical considerations of who is available to participate!
The type of statistical analysis you do will depend on the sample type you have. Most importantly, you cannot generalise your findings to the population as a whole if you do not have a random sample. You can still undertake some inferential statistical analysis but you should report these as results of your sample, not as applicable to the population at large.
Common sampling approaches include:
- Random sampling
- Stratified sampling
- Cluster sampling
- Convenience sampling
- Accidental sampling
