I think you mean ordinal data. Similar to the Golf tournament, you need to determine where to "cut" (from the ordinal data) so as to divide the data into different categories (to the nominal data).
For example, if the ordinal data range from 1 to 6 (where 1 = the best) and the cut is 3, then you convert all the numbers from 1 to 3 to "1" (which represents "good") and the all numbers from 4 to 6 to "2" (which represents "bad"). In other words, 1, 2, and 3 from the original ordinal data set are converted to "1" (ordinal data); whereas 4, 5, and 6 from the original date set now become "2" (ordinal data).
Eddie T.C. Lam
nominal
Yes, marital status is nominal data.
They are part of nominal data if the study is about different kinds of methods for displaying statistical data.
Occupation is nominal data. There is not an order to the category occupation, so that eliminates ordinal and interval.
Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.
Yes, marital status is nominal data.
No, it is not suitable for nominal data.
If you are bothering to measure it, it probably is not nominal data in your study.
nominal
Yes, marital status is nominal data.
In qualitative variables, nominal data involves categories with no inherent order, such as colors or types of fruit. Ordinal data, on the other hand, includes categories that have a meaningful order or ranking, such as education levels or customer satisfaction ratings.
They are part of nominal data if the study is about different kinds of methods for displaying statistical data.
Nominal
Nominal or categoric data.
illustrate how you can express the age of group of persons as {1}nominal,{2}ordinal data,{3} interval data,{4}ratio data
Occupation is nominal data. There is not an order to the category occupation, so that eliminates ordinal and interval.
Gender is nominal. Nominal is categorical only; no ordering scheme. Ordinal level of measurement places some order on the data, but the differences between the data can't be determined or are meaningless.