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Let's Talk Data: 4 Variable Types

  • 02-06-2014 10:58am
    #1
    Black Swan
    Moderators, Category Moderators, Science, Health & Environment Moderators, Society & Culture Moderators Posts: 47,300 CMod ✭✭✭✭


    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?


Comments

  • #2
    Sciscitatio
    Registered Users, Registered Users 2 Posts: 66 ✭✭Sciscitatio


    This is why I like qualitative research more then quan. :)


  • #3
    Black Swan
    Moderators, Category Moderators, Science, Health & Environment Moderators, Society & Culture Moderators Posts: 47,300 CMod ✭✭✭✭Black Swan


    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).


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