Calculating Linear Regressions or Correlation Coefficients

       
mysql>
mysql> CREATE TABLE testscore
    -> (
    ->  subject INT UNSIGNED NOT NULL AUTO_INCREMENT,
    ->  age             INT UNSIGNED NOT NULL,
    ->  sex             ENUM('M','F') NOT NULL,
    ->  score   INT,
    ->  PRIMARY KEY (subject)
    -> );
Query OK, 0 rows affected (0.01 sec)

mysql>
mysql> INSERT INTO testscore (age,sex,score)
    ->  VALUES
    ->  (5,'M',5),
    ->  (5,'M',4),
    ->  (5,'F',6),
    ->  (5,'F',7),
    ->  (6,'M',8),
    ->  (6,'M',9),
    ->  (6,'F',4),
    ->  (6,'F',6),
    ->  (7,'M',8),
    ->  (7,'M',6),
    ->  (7,'F',9),
    ->  (7,'F',7),
    ->  (8,'M',9),
    ->  (8,'M',6),
    ->  (8,'F',7),
    ->  (8,'F',10),
    ->  (9,'M',9),
    ->  (9,'M',7),
    ->  (9,'F',10),
    ->  (9,'F',9)
    -> ;
Query OK, 20 rows affected (0.00 sec)
Records: 20  Duplicates: 0  Warnings: 0

mysql>
mysql> SELECT subject, age, sex, score FROM testscore ORDER BY subject;
+---------+-----+-----+-------+
| subject | age | sex | score |
+---------+-----+-----+-------+
|       1 |   5 | M   |     5 |
|       2 |   5 | M   |     4 |
|       3 |   5 | F   |     6 |
|       4 |   5 | F   |     7 |
|       5 |   6 | M   |     8 |
|       6 |   6 | M   |     9 |
|       7 |   6 | F   |     4 |
|       8 |   6 | F   |     6 |
|       9 |   7 | M   |     8 |
|      10 |   7 | M   |     6 |
|      11 |   7 | F   |     9 |
|      12 |   7 | F   |     7 |
|      13 |   8 | M   |     9 |
|      14 |   8 | M   |     6 |
|      15 |   8 | F   |     7 |
|      16 |   8 | F   |    10 |
|      17 |   9 | M   |     9 |
|      18 |   9 | M   |     7 |
|      19 |   9 | F   |    10 |
|      20 |   9 | F   |     9 |
+---------+-----+-----+-------+
20 rows in set (0.00 sec)

mysql>
mysql> SELECT
    -> @n := COUNT(score) AS N,
    -> @meanX := AVG(age) AS "X mean",
    -> @sumX := SUM(age) AS "X sum",
    -> @sumXX := SUM(age*age) "X sum of squares",
    -> @meanY := AVG(score) AS "Y mean",
    -> @sumY := SUM(score) AS "Y sum",
    -> @sumYY := SUM(score*score) "Y sum of square",
    -> @sumXY := SUM(age*score) AS "X*Y sum"
    -> FROM testscore\G
*************************** 1. row ***************************
               N: 20
          X mean: 7.000000000
           X sum: 140
X sum of squares: 1020
          Y mean: 7.300000000
           Y sum: 146
 Y sum of square: 1130
         X*Y sum: 1053
1 row in set (0.00 sec)

mysql>
mysql>
mysql> drop table testscore;
Query OK, 0 rows affected (0.00 sec)

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Calculating Linear Regressions or Correlation Coefficients : Variable « Select Clause « SQL / MySQL

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