Question

Determine Whether the qualitative variable is nominal or ordinal

Make of a Car

Is the variable nominal or ordinal?

Answer 1

Nominal

Answer 2

i think nominal....read it
Nominal Variables
Nominal variables allow for only qualitative classification. That is, they can be measured only in terms of whether the individual items belong to certain distinct categories, but we cannot quantify or even rank order the categories: Nominal data has no order, and the assignment of numbers to categories is purely arbitrary. Because of lack of order or equal intervals, one cannot perform arithmetic (+, -, /, *) or logical operations (>, <, =) on the nominal data. Typical examples of such variables are:

Gender:
1. Male
2. Female

Marital Status:
1. Unmarried
2. Married
3. Divorcee
4. Widower




Ordinal Variables
A discrete ordinal variable is a nominal variable, but its different states are ordered in a meaningful sequence. Ordinal data has order, but the intervals between scale points may be uneven. Because of lack of equal distances, arithmetic operations are impossible, but logical operations can be performed on the ordinal data. A typical example of an ordinal variable is the socio-economic status of families. We know 'upper middle' is higher than 'middle' but we cannot say 'how much higher'. Ordinal variables are quite useful for subjective assessment of 'quality; importance or relevance'. Ordinal scale data are very frequently used in social and behavioral research. Almost all opinion surveys today request answers on three-, five-, or seven- point scales. Such data are not appropriate for analysis by classical techniques, because the numbers are comparable only in terms of relative magnitude, not actual magnitude.

Consider for example a questionnaire item on the time involvement of scientists in the 'perception and identification of research problems'. The respondents were asked to indicate their involvement by selecting one of the following codes:

1 = Very low or nil
2 = Low
3 = Medium
4 = Great
5 = Very great

Here, the variable 'Time Involvement' is an ordinal variable with 5 states.

Ordinal variables often cause confusion in data analysis. Some statisticians treat them as nominal variables. Other statisticians treat them as interval scale variables, assuming that the underlying scale is continuous, but because of the lack of a sophisticated instrument, they could not be measured on an interval scale.

Answer 3

thank you both.