I record all the tricks here to determine a qualitative (categorical), quantitative, nominal, ordinal, discrete, and continuous variable.
First, two main groups of variables are qualitative and quantitative. In order to distinguish them, the criterion is “Can the answers of a variable be added?” For instance, you are concerning what is in your shopping bag. The bag contains oranges and apples (Answers). Since orange and apple can not be added, the list of items in your bag is a qualitative data. However, if you are counting apples in the bag. The data will be quantitative, say 2+3(=5) apples.
For qualitative data, if the list can be sorted naturally, we further specify it as an ordinal variable. Otherwise, the variable is nominal. For example, you can not have a natural order for apple, orange, and banana. The list of fruit is nominal. On the other hand, a Likert scale for answering whether you like to eat fruit is ordinal: Dislike, Neither like nor dislike, like.
Two subgroups are in quantitative data as well, discrete and continuous. The criterion for distinguishing them is “Could a decimal number be an answer?” For examples, if you are counting how many people in a theater, you can not have a number such as 3.14. The number of people in a theater is discrete. However, if you consider the average people in a theater per show, the number 3.14 could be an answer; the average people in a theater per show is continuous.
- Qualitative (can NOT be added)
- Nominal (can NOT have a natural order)
- Ordinal (can be sorted naturally)
- Quantitative (can be added)
- Discrete (decimals does NOT “make sense”)
- Continuous (decimals “makes sense”)