# Basic Statistics : Types of Variables

Types of Variables

In the image shown below, we are showing the different types of variables in statistics.

Categorical Variables

Qualitative data are often termed categorical data. Data that can be added into categories according to their characteristics. Categorical variables can be classified into two types: Nominal Variables and Ordinal Variables.

Nominal Variable

A variable that has two or more categories, without any implied ordering.

Examples of Nominal Variables
• Gender - Male, Female
• Marital Status - Unmarried, Married, Divorcee
• State - Texas, New Delhi, Illinois, Michigan
Ordinal Variable (Ordered list)

A variable that has two or more categories, with clear ordering.

Examples of Ordinal Variables
• Scale - Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree
• Rating - Very low, Low, Medium, Great, Very great
Numeric Variables

Numeric variables can be classified into two types: Interval variables and Ratio variables.

Interval Variable

In statistics, intervals mean the set of values between two numbers. An interval variable is similar to an ordinal variable except that the intervals between the values of the interval variable are equally spaced. In other words, it has order and equal intervals.

Examples of Interval Variables
• Temperature in Celsius - Temperature of 30°C is higher than 20°C and temperature of 20°C is higher than 10°C. The size of these intervals is the same.
• Dates - The difference between 1st March and 1st April is the same as between 1st May and 1st June.
Ratio Variable

It is interval data with a natural zero point. When the variable equals 0.0, there is none of that variable.

Examples of Ratio Variables
• Height
• Weight
• Temperature in Kelvin - It is a ratio variable, as 0.0 Kelvin really means 'no temperature'.
• Number of Patients in a Hospital.

Explanation : A weight of zero means no mass. We can also compare weights. For example, someone weighing 80 kilograms is double the weight of someone weighing 40 kilograms.

Types of Ratio Variable

Ratio variables can be continuous or discrete.

Discrete Variable Continuous Variable
Values that you cannot divide Any value within a range
Count Data Measurable Data
Continuous Variables

Continuous variables can take on any value within a range. Examples : Height, weight, temperature (in Kelvin) are all continuous variables.

Annual Income is a continuous variable because it can take on any value within a certain range.

Discrete Variables

Discrete Variables can only take on whole values within a range. It means you can count the possible values. Examples : Number of siblings, number of nurses in a hospital, results of a coin toss are all discrete variables.

Related Posts
Share

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and HR.

Post Comment 18 Responses to "Basic Statistics : Types of Variables"
1. so simple.is written in an understandable form

2. A very good start for the beginners to continue their journey till they become master

3. very well crafted for beginners to become master it.

4. Really great approach to learn statistics in easy way and understandable format

5. So a ratio is a subtype of interval data : may you correct the tree chart ?

6. Really good explanation!

7. Easy to understand

8. Good Explanation

9. Good Explanation & easy to understand

10. Thank u for good understandable points

11. It's perfect!

12. Simple and clear!

13. It's rather confusing that ratio data type is also interval data type with natural zero point. The example given were height and weight. The reason it's confusing is because height and weight are both continuous (as opposed to discrete) data type, meaning they could have infinite number of decimal points, that said, if they are also "interval" data type, what are their intervals ?

1. In ratio variables, the intervals mean the difference between two values. We can compare height and weight. For example, someone weighing 80 kilograms is double the weight of someone weighing 40 kilograms. Ratio variables can be either continuous or discrete. Weight is a continuous ratio variable.

Next → ← Prev