Statistical analysis for social scientists very often means statistical analysis of some questionnaire data. The meaning of the numbers obtained in such analyses depends very much on the kind of scales used. In this paper it is shown that the meaning of numbers can also depend on how exactly the scales are constructed. First, some background information about how scales of the same type (e.g., interval scales) can considerably differ in meaning is given and then a series of study results with interval, ordinal, and nominal scales that demonstrate these differential effects are reported. It is argued that such results can easily be replicated in statistics classes. It is further argued that due to the preponderance of scales in social science research, statistics courses should put an emphasis on teaching the correct use and interpretation of scales. Here, demonstrations such as the ones described in this paper can play a helpful role.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education