Data Type
Analyze data according to data type
Qualitative data, like text in a book or interviews, requires human interpretation.
Quantitative data, being numbers, can use statistics, which again vary with data type:
a) Categorical, a set of categories, like PC, laptop, handheld.
b) Ordinal, a series of ranks, like 1st, 2nd, 3rd, etc,
c) Interval, a number series like 1, 2, 3,...
Changing data type changes data power, e. g. measuring computer experience in years (interval data) gives more information than self-ratings of Expert, Competent or Novice (categorical), as the latter involves fewer choices. Yet the latter may be more realistic, as many years may not make one an expert.
Example(s)
(Use a descriptive name, e. g. "ITExample". Or click on an existing collection and edit it.)