SQL Server/T-SQL Tutorial/Analytical Functions/VAR

The VAR() return the measure of how far the extreme low range or high range value is from the middle

or mean value of the range, weighted by the greatest concentration of similar values.
11>
12> Create Table MyValues (MyValue Float)
13> GO
1>
2> Insert Into MyValues (MyValue) SELECT 2
3> Insert Into MyValues (MyValue) SELECT 3
4> Insert Into MyValues (MyValue) SELECT 4
5> Insert Into MyValues (MyValue) SELECT 5
6> Insert Into MyValues (MyValue) SELECT 6
7> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2> SELECT VAR(MyValue) FROM MyValues
3> GO
------------------------
                     2.5
(1 rows affected)
1>
2> INSERT INTO MyValues (MyValue) SELECT 3
3> INSERT INTO MyValues (MyValue) SELECT 4
4> INSERT INTO MyValues (MyValue) SELECT 4
5> INSERT INTO MyValues (MyValue) SELECT 4
6> INSERT INTO MyValues (MyValue) SELECT 5
7> GO
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
(1 rows affected)
1>
2> SELECT VAR(MyValue) FROM MyValues
3> GO
------------------------
      1.3333333333333333
(1 rows affected)
1>
2>
3> drop table MyValues;
4> GO

VAR computes the variance of all the values listed in a column or expression.

The aggregate function VARP computes the variance for the population of all the values listed in a column or expression.
11>
12> CREATE TABLE employee(
13>    id          INTEGER NOT NULL PRIMARY KEY,
14>    first_name  VARCHAR(10),
15>    last_name   VARCHAR(10),
16>    salary      DECIMAL(10,2),
17>    start_Date  DATETIME,
18>    region      VARCHAR(10),
19>    city        VARCHAR(20),
20>    managerid   INTEGER
21> );
22> GO
1> INSERT INTO employee VALUES (1, "Jason" ,  "Martin", 5890,"2005-03-22","North","Vancouver",3);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (2, "Alison",  "Mathews",4789,"2003-07-21","South","Utown",4);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (3, "James" ,  "Smith",  6678,"2001-12-01","North","Paris",5);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (4, "Celia" ,  "Rice",   5567,"2006-03-03","South","London",6);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (5, "Robert",  "Black",  4467,"2004-07-02","East","Newton",7);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (6, "Linda" ,  "Green" , 6456,"2002-05-19","East","Calgary",8);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (7, "David" ,  "Larry",  5345,"2008-03-18","West","New York",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (8, "James" ,  "Cat",    4234,"2007-07-17","West","Regina",9);
2> GO
(1 rows affected)
1> INSERT INTO employee VALUES (9, "Joan"  ,  "Act",    6123,"2001-04-16","North","Toronto",10);
2> GO
(1 rows affected)
1>
2> select * from employee;
3> GO
id          first_name last_name  salary       start_Date              region     city                 managerid
----------- ---------- ---------- ------------ ----------------------- ---------- -------------------- -----------
          1 Jason      Martin          5890.00 2005-03-22 00:00:00.000 North      Vancouver                      3
          2 Alison     Mathews         4789.00 2003-07-21 00:00:00.000 South      Utown                          4
          3 James      Smith           6678.00 2001-12-01 00:00:00.000 North      Paris                          5
          4 Celia      Rice            5567.00 2006-03-03 00:00:00.000 South      London                         6
          5 Robert     Black           4467.00 2004-07-02 00:00:00.000 East       Newton                         7
          6 Linda      Green           6456.00 2002-05-19 00:00:00.000 East       Calgary                        8
          7 David      Larry           5345.00 2008-03-18 00:00:00.000 West       New York                       9
          8 James      Cat             4234.00 2007-07-17 00:00:00.000 West       Regina                         9
          9 Joan       Act             6123.00 2001-04-16 00:00:00.000 North      Toronto                       10
(9 rows affected)
1>
2> SELECT VAR(salary) variance_of_budgets
3>        FROM employee
4>
5>
6>
7> drop table employee;
8> GO
variance_of_budgets
------------------------
      755682.77777777612
(1 rows affected)
1>