Statistical Functions in SQL

SQL Statistical Functions are built-in functions that help analyze numeric data by performing calculations like averages, totals and variations. They are widely used to extract meaningful insights from database records.

• Perform calculations like AVG, SUM, COUNT, MIN, MAX
• Help measure data spread using STDDEV and VAR
• Used for quick data analysis and reporting

Statistical Functions in SQL

Here are Some Common Statistical Functions in SQL

Working with Statistical Functions

We consider the following four tables for the examples below: 'studentdetails,' 'employees,' 'sales_data,' and 'financial_data.'

1. AVG() Function

AVG() calculates the average or arithmetic mean for a group of numbers or a numeric column.

Syntax:

SELECT AVG(column_name) FROM table_name;

Query:

SELECT AVG(marks) AS average_marks FROM studentdetails

Output:

2. SUM() Function

SUM() function returns the total of all numeric values in a column.

Syntax:

SELECT SUM(column_name) FROM table_name;

Query:

SELECT SUM(marks) AS total_marks FROM studentdetails;

Output:

3. Count() Function

COUNT() function counts the number of rows in a result set or the number of non-NULL numeric values in a column.

Syntax:

SELECT COUNT(*) FROM table_name;
SELECT COUNT(column_name) FROM table_name;

• COUNT(*) counts all rows, including rows with NULL values.
• COUNT(column_name) counts only non-NULL values in that column.

Query:

SELECT COUNT(studentID) AS total_students FROM studentdetails;
SELECT COUNT(*) FROM studentdetails;

Output:

4. Max() Function

MAX() function returns the largest value from a numeric or date column.

Syntax:

SELECT MAX(column_name) FROM table_name;

Query:

SELECT MAX(marks) AS highest_marks FROM studentdetails;

Output:

5. MIN() Function

MIN() function returns the smallest value from a numeric or date column.

Syntax:

SELECT MIN(column_name) FROM table_name;

Query:

SELECT MIN(marks) AS lowest_marks FROM studentdetails;

Output:

6. VAR() / VARIANCE() Function

VAR() / VARIANCE() functions calculate the variance of numeric data, measuring how much the values spread out from the average.

Syntax:

SELECT VAR(column_name) FROM table_name;

Query:

SELECT VARIANCE(marks) AS variance_marks FROM studentdetails;

Output:

7. STDDEV() / STDDEV_POP() Function

STDDEV() / STDDEV_POP() functions calculate the standard deviation of numeric data to measure how much the values deviate from the average.

Syntax:

SELECT STDDEV(column_name) FROM table_name;

Query:

SELECT STDDEV(marks) AS stddev_marks FROM studentdetails;

Output:

8. PERCENTILE_CONT() Function

PERCENTILE_CONT() function returns a continuous percentile value (such as the median) by interpolating results within an ordered dataset.

Syntax:

SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY column_name) FROM table_name;

Query:

SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY salary) AS median_salary
FROM employees;

Output:

9. CORR() Function

CORR() function calculates the correlation coefficient between two numeric columns, showing the strength and direction of their linear relationship.

Syntax:

SELECT CORR(column1, column2) FROM table_name;

Query:

SELECT CORR(sales, profit) AS correlation_coefficient
FROM sales_data;

Output:

10 .COVAR_POP() Function

The COVAR_POP() function computes the population covariance between two numeric columns, helping measure how the values change in relation to each other.

Syntax:

SELECT COVAR_POP(column1, column2) FROM table_name;

Query:

SELECT COVAR_POP(revenue, expenses) AS population_covariance
FROM financial_data;

Output: