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SQL Server RunningCORREL Function

Updated 2023-11-14 14:16:11.977000

Description

Use the the scalar function RunningCORREL to calculate the Pearson product moment correlation coefficient through data points in y- and x-values within a resultant table or partition, without the need for a self-join. The correlation coefficient is calculated from the first row of the resultant table or partition through to the current row. If the column values are presented to the functions out of order, an error message will be generated.

Syntax

SELECT [westclintech].[wct].[RunningCORREL](
  <@Y, float,>
 ,<@X, float,>
 ,<@RowNum, int,>
 ,<@Id, tinyint,>)

Arguments

@Y

the y-value passed into the function. @Y is an expression of type float or of a type that can be implicitly converted to float.

@X

the x-value passed into the function. @X is an expression of type float or of a type that can be implicitly converted to float.

@RowNum

the number of the row within the group for which the sum is being calculated. If @RowNum for the current row in a set is less than or equal to the previous @RowNum and @RowNum is not equal to 1, an error message will be generated. @RowNum is an expression of type int or of a type that can be implicitly converted to int.

@Id

a unique identifier for the RunningCORREL calculation. @Id allows you to specify multiple RunningCORREL calculations within a resultant table. @Id is an expression of type tinyint or of a type that can be implicitly converted to tinyint.

Return Type

float

Remarks

If @Id is NULL then @Id = 0.

@RowNum must be in ascending order.

To calculate the correlation coefficient over a window of x- and y-values use the MovingCORREL function.

If @RowNum = 1 then RunningCORREL is NULL.

To calculate a single correlation coefficient for a set, use the CORREL function.

There may be cases where the order in which the data are returned to the function and the order in which the results are returned are different, generally due to parallelism. You can use OPTION(MAXDOP 1) or OPTION(MAXDOP 1,FORCE ORDER) to help eliminate this problem.

Examples

In this example we will calculate the correlation coefficient in the relationship between square footage and house prices. We will create a temporary table, #se, populate it with some data and then run the SELECT.

SET NOCOUNT ON;
--Create the temporary table
CREATE TABLE #se
(
    rn int,
    id_lot int,
    amt_sqft int,
    amt_price int,
    PRIMARY KEY (rn)
);
--Put some date in the table
INSERT INTO #se
VALUES
(1, 21783, 1147, 393918);
INSERT INTO #se
VALUES
(2, 94729, 1313, 470479);
INSERT INTO #se
VALUES
(3, 33028, 1433, 512474);
INSERT INTO #se
VALUES
(4, 59446, 1724, 610477);
INSERT INTO #se
VALUES
(5, 97646, 1162, 388196);
INSERT INTO #se
VALUES
(6, 44823, 1813, 636916);
INSERT INTO #se
VALUES
(7, 88397, 1105, 374348);
INSERT INTO #se
VALUES
(8, 13588, 1555, 559149);
INSERT INTO #se
VALUES
(9, 13891, 1775, 623900);
INSERT INTO #se
VALUES
(10, 90957, 1585, 563947);
INSERT INTO #se
VALUES
(11, 44167, 1510, 529806);
INSERT INTO #se
VALUES
(12, 75533, 1628, 592533);
INSERT INTO #se
VALUES
(13, 56812, 1145, 408634);
INSERT INTO #se
VALUES
(14, 12897, 1632, 589522);
INSERT INTO #se
VALUES
(15, 93826, 1850, 668852);
INSERT INTO #se
VALUES
(16, 74510, 1867, 633400);
INSERT INTO #se
VALUES
(17, 17262, 1587, 552178);
INSERT INTO #se
VALUES
(18, 30929, 1809, 633141);
INSERT INTO #se
VALUES
(19, 49030, 1521, 555713);
INSERT INTO #se
VALUES
(20, 33431, 1195, 434542);
--Calculate CORREL
SELECT rn,
       id_lot,
       amt_sqft,
       amt_price,
       wct.RunningCORREL(amt_price, amt_sqft, ROW_NUMBER() OVER (ORDER BY rn), 
                 NULL) as CORREL
FROM #se;
--Clean up
DROP TABLE #se;

This produces the following result.

rnid_lotamt_sqftamt_priceCORREL
1217831147393918NULL
29472913134704791
33302814335124740.997250449708387
45944617246104770.996692220392964
59764611623881960.994211415947064
64482318136369160.995557722348421
78839711053743480.996267358109546
81358815555591490.995765872256083
91389117756239000.996158306680619
109095715855639470.996171484656381
114416715105298060.996164248562469
127553316285925330.99511276733915
135681211454086340.994933340316737
141289716325895220.994769382190739
159382618506688520.995452352061868
167451018676334000.992009513311456
171726215875521780.991773410568987
183092918096331410.992042626769922
194903015215557130.990858779380213
203343111954345420.990792688204407