Is it possible to calculate a correlation in a MySQL query?

Yes, it is possible to calculate a correlation in a query. To understand the correlation in a query, you need to first create a table. The query to create a table is as follows

mysql> create table correlationDemo - > ( - > value float not null, - > value2 float not null - > ); Query OK, 0 rows affected (0.62 sec)

Insert some records in the table with the help of insert command. The query is as follows to insert records in the table

mysql> insert into correlationDemo values(1,10); Query OK, 1 row affected (0.19 sec) mysql> insert into correlationDemo values(2,4); Query OK, 1 row affected (0.16 sec) mysql> insert into correlationDemo values(3,5); Query OK, 1 row affected (0.14 sec) mysql> insert into correlationDemo values(6,17); Query OK, 1 row affected (0.16 sec)

Display all records from the table using select statement.

The query is as follows

mysql> select *from correlationDemo;

The following is the output

+-------+--------+ | value | value2 | +-------+--------+ | 1 | 10 | | 2 | 4 | | 3 | 5 | | 6 | 17 | +-------+--------+ 4 rows in set (0.03 sec)

Now here is the simple correlation in a query

mysql> select @firstValue:=avg(value), - > @secondValue:=avg(value2), - > @division:=(stddev_samp(value) * stddev_samp(value2)) from correlationDemo;

The following is the output

+-------------------------+---------------------------+-------------------------------------------------------+ | @firstValue:=avg(value) | @secondValue:=avg(value2) | @division:=(stddev_samp(value) *stddev_samp(value2)) | +-------------------------+---------------------------+-------------------------------------------------------+ | 3 | 9 | 12.84090685617215 | +-------------------------+---------------------------+-------------------------------------------------------+ 1 row in set (0.00 sec)

Here is the calculation of the above correlation query

mysql> select sum( ( value - @firstValue ) * (value2 - @secondValue) ) / ((count(value) -1) * @division) from - > correlationDemo;

The following is the output

+--------------------------------------------------------------------------------------------+ | sum( ( value - @firstValue ) * (value2 - @secondValue) ) / ((count(value) -1) * @division) | +--------------------------------------------------------------------------------------------+ | 0.7008850777290727 | +--------------------------------------------------------------------------------------------+ 1 row in set (0.00 sec)