Distribution qualitative nominale

data categories including characteristics, for example, names, ages, locations and occupations or personal preferences, for example, food, clothes and leisure activities. • also called qualitative dat [..]

Training data that assigns a text value to individual examples. Query results try to find the label (category) that the query term most closely resembles. For instance, the Hello World example tries t [..]

n. types of data which can be counted and divided into groups. Thus, they consist of counts in contrast to that which relates to measurements. Data of this kind include those which can be grouped (or [..]

The data of counts as opposed to measurements such as religion. Also called nominal data.

Variables with discrete, non-numeric or qualitative categories (e.g. gender or marital status). The categories can be given numerical codes, but they cannot be ranked, added, multiplied or measured ag [..]

Non-numerical data sets are categorical. For example, the responses to “What month were you born?” are categorical data. Frequency counts can be made of the values for a given category. The table belo [..]

Consists of data that can be grouped by specific categories (also known as qualitative variables). Categorical variables may have categories that are naturally ordered (ordinal variables) or have no n [..]

Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of ...

Data that are classified into two or more non-overlapping categories. Race and type of drug (aspirin, paracetamol, etc.) are examples of categorical variables. If there is a natural order to the categories, for example, non-smokers, ex-smokers, light smokers and heavy smokers, the data are known as ordinal data. If there are only two categories, th [..]