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Variable: A variable is an entity that varies from a place to place, a person to person, a trial to trial and so on. For instance the height is a variable; domicile is a variable since they vary from person to person.

A variable is said to be quantitative if it is measurable and can be expressed in specific units of measurement (numbers).

A variable is said to be qualitative if it is not measurable and cannot be expressed in specific units of measurement (numbers). This variable is also called categorical variable.

Most variables in a data set can be classified into one of two major types.

Numerical variables

The values of a numerical variable are numbers. They can be further classified into discrete and continuous variables.

**Discrete numerical variable :-** A variable whose values are whole numbers (counts) is called discrete. For example, the number of items bought by a customer in a supermarket is discrete.

**Continuous numerical variable :** A variable that may contain any value within some range is called continuous. For example, the time that the customer spends in the supermarket is continuous.

Categorical variables

The values of a categorical variable are selected from a small group of categories. Examples are gender (male or female) and marital status (never married, married, divorced or widowed).

Categorical variables can be further categorised into ordinal and nominal variables.

**Ordinal categorical variable:-** A categorical variable whose categories can be meaningfully ordered is called ordinal. For example, a student’s grade in an exam (A, B, C or Fail) is ordinal.

**Nominal categorical variable :–**It does not matter which way the categories are ordered in tabular or graphical displays of the data — all orderings are equally meaningful. For example, a student’s religion (Atheist, Christian, Muslim, Hindu, …) is nominal.

Quantitative Data:

Quantitative data (variable are measurements that are collected or recorded as a number. Apart from the usual data like height, weight etc.,

Qualitative Data:

Qualitative data are measurements that cannot be measured on a natural numerical scale. For example, the blood types are categorized as O, A, B along with the Rh factors. They can only be classified into one of the pre assigned or pre designated categories.