Key concepts

Nominal scales are used for labeling variables, without any quantitative value.  “Nominal” scales could simply be called “labels.”  Here are some examples, below.  Notice that all of these scales are mutually exclusive (no overlap) and none of them have any numerical significance.  A good way to remember all of this is that “nominal” sounds a lot like “name” and nominal scales are kind of like “names” or labels.

(Statistics) a discrete classification of data, in which data are neither measured nor ordered but subjects are merely allocated to distinct categories: for example, a record of students' course choices constitutes nominal data which could be correlated with school results

The nominal scale (also called dummy coding) simply places people, events, perceptions, etc. into categories based on some common trait.

Nominal scale is a measurement scale which are used for labeling variables, without any quantitative value.  “Nominal” scales could simply be called “labels.”

A nominal scale, as the name implies, is simply some placing of data into categories, without any order or structure.

a discrete classification of data, in which data are neither measured nor ordered but subjects are merely allocated to distinct categories: for example, a record of students' course choices constitutes nominal data which could be correlated with school results

• • The lowest measurement level you can use, from a statistical point of view, is a nominal scale.A nominal scale, as the name implies, is simply some placing of data into categories, without any order or structure.

• • The lowest measurement level you can use, from a statistical point of view, is a nominal scale.A nominal scale, as the name implies, is simply some placing of data into categories, without any order or structure.

• • The lowest measurement level you can use, from a statistical point of view, is a nominal scale.A nominal scale, as the name implies, is simply some placing of data into categories, without any order or structure.

The nominal scale is often called qualitative scales. This type is used for distinguishing between items or subjects based only on their names or categories and other qualitative classifications they belong to; thus, the different data involves the construction of classifications as well as the classification of items.  Numbers may be used to represent the variables but the numbers do not have numerical value or relationship. For example: In grammar, the parts of speech: noun, verb, preposition, article, pronoun, etc