MySQL VAR_SAMP is one of the Aggregate Function, which is used to calculate the Sample Variance of total records (or rows) selected by the SELECT Statement.

## MySQL VAR_SAMP Formula

The mathematical formula behind the VAR_SAMP to calculate the sample variance is as shown below:

--Calculating Mean or Average Mean = Sum of each individual / Total number of items --Calculating the Sample Variance Sample Variance = ( (OriginalValue – Mean)² + (OriginalValue – Mean)² +.... ) / (Total number of items - 1)

### MySQL VAR_SAMP Syntax

The basic syntax behind the VAR_SAMP function in MySQL is as shown below:

-- VAR_SAMP in MySQL Syntax SELECT VAR_SAMP(Column_Name) FROM Source;

In this article we will show you, How to write VAR_SAMP function in MySQL to calculate the sample Variance with example. For this, We are going to use the below shown data

## MySQL VAR_SAMP Example

The VAR_SAMP function will simply returns the Simple Variance of total records present in a specified column.

For example, below query will calculate the Sample Variance of all the records present in Yearly_Income from Customer details table.

-- MySQL VAR_SAMP example SELECT VAR_SAMP(Yearly_Income) AS `Simple income Variance` FROM customerdetails;

**OUTPUT**

## MySQL VAR_SAMP – Group By Example

In general, VAR_SAMP function is used to calculate the Sample Variance of a products belongs to particular category or color etc. In this situation you can use GROUP BY Clause to group the products by category. And next, use VAR_SAMP Function to calculate the Sample Variance

-- MySQL VAR_SAMP Function Example USE company; SELECT Profession, VAR_SAMP(Yearly_Income) FROM customerdetails GROUP BY Profession;

Above SQL Query will group the Customers by their Profession, and calculates their Sample Variance

**OUTPUT**

**ANALYSIS**

For this demonstration, We are taking Software Developer profession, and show you the output.

— Calculating Mean

Mean = (70000 + 79,000) / 2

Mean = 74,500

— Calculating Sample Variance

Variance = (70,000 – 74,500)² + (79,000 – 74,500)² / (2-1)

Variance = 40,500,000

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