Many statistics books begin by defining the different kinds of variables you might want to analyze. This scheme was developed by S. Stevens and published in 1946.
A categorical variable, also called a nominal variable, is for mutually exclusive, but not
Many statistics books begin by defining the different kinds of variables you might want to analyze. This scheme was developed by S. Stevens and published in 1946.
A categorical variable, also called a nominal variable, is for mutually exclusive, but not ordered, categories. For example, your study might compare five different genotypes. You can code the five genotypes with numbers if you want, but the order is arbitrary and any calculations (for example, computing an average) would be meaningless.
An ordinal variable, is one where the order matters but not the difference between values. For example, you might ask patients to express the amount of pain they are feeling on a scale of 1 to 10. A score of 7 means more pain than a score of 5, and that is more than a score of 3. But the difference between the 7 and the 5 may not be the same as that between 5 and 3. The values simply express an order. Another example would be movie ratings, from * to *****.
An interval variable is a one where the difference between two values is meaningful. The difference between a temperature of 100 degrees and 90 degrees is the same difference as between 90 degrees and 80 degrees.
A ratio variable, has all the properties of an interval variab