Let's Talk Data: 4 Variable Types

I've always operated under the assumption that there were only 4 data variable types: nominal, ordinal, interval, and ratio. Examples:

• Nominal: Mutually exclusive categories (e.g., either/or; male or female; right or wrong; true or false).
• Ordinal: Greater or lesser than; ordered but unequal intervals (e.g., Richter magnitude scale; Gleason prostate cancer score grade 1-5; medical pain scale from 1-10; semantic differential scale; Likert opinion scale).
• Interval: Precisely measured equal intervals, but arbitrary zero point (e.g., Celsius and Fahrenheit temperature scales; latitude; longitude).
• Ratio: Precisely measured equal intervals with absolute zero (e.g., height; weight; euros).

Why important? The variable data type, along with other considerations, suggests what statistical formula would be appropriate for data analysis.

What am I missing? Comments? Suggestions?

Sciscitatio

This is why I like qualitative research more then quan.

Sciscitatio

Sciscitatio wrote: »

This is why I like qualitative research more then quan.

If done rigorously, qualitative research methods are not a walk in the park. I would suggest that you read Hortense Powdermaker's Stranger and Friend (1967) wherein she discusses 5 major pieces of fieldwork in 5 chapters, especially the Hollywood study that was a complete methodological disaster (by her own admission).