TRIMMEAN
Updated: 28 February 2011
Note: This documentation is for the SQL2008 (and later) version of this XLeratorDB function, it is not compatible with SQL Server 2005.
Click here for the SQL2005 version of the TRIMMEAN function
Use TRIMMEAN to calculate the mean of the interior of a dataset. TRIMMEAN calculates the mean taken by excluding a percentage of data points from the top and bottom tails of a dataset.Syntax
Arguments
@known_x
The values to be used in the TRIMMEAN calculation. @known_x is an expression of type float or of a type that can be implicitly converted to float.
@percent
is the fractional number of data points to exclude from the calculation. For example, if percent = 0.2, 4 points are trimmed from a dataset of 20 points (20 x 0.2): 2 from the top and 2 from the bottom of the set. @percent is an expression of type float or of a type that can be implicitly converted to float.
Return Types
float
Remarks
· If @percent < 0 or @Percent > 1, TRIMMEAN returns an error.
· TRIMMEAN rounds the number of excluded data points down to the nearest multiple of 2. If percent = 0.1, 10 percent of 30 data points equals 3 points. For symmetry, TRIMMEAN excludes a single value from the top and bottom of the dataset.
· NULL values are not included in the standard deviation calculation.
· TRIMMEAN is an aggregate function and follows the same conventions as all other aggregate functions in SQL Server.
· If you have previously used the TRIMMEAN scalar function, the TRIMMEAN aggregate has a different syntax. The TRIMMEAN scalar function is no longer available in XLeratorDB/statistics2008, though you can still use the scalar TRIMMEAN _q.
Examples
In this example, we calculate the mean for selected salary inforrmation collected from 10 cities, trimming the top and bottom 10%.
SELECT wct.TRIMMEAN(
salary --@known_x
,.10 --@percent
) as TRIMMEAN
FROM (VALUES
('New York','429-00-6486',236503),
('New York','90-70-2526',224472),
('New York','87-85-0404',139802),
('New York','716-89-3089',185287),
('New York','159-78-5370',211900),
('New York','195-97-6820',186703),
('New York','95-49-2813',167451),
('New York','37-20-7422',149462),
('New York','44-48-0076',214708),
('New York','514-79-0041',226485),
('Los Angeles','526-34-4521',196402),
('Los Angeles','800-50-0868',205359),
('Los Angeles','41-34-3618',195679),
('Los Angeles','854-29-9398',131925),
('Los Angeles','673-30-3623',171091),
('Los Angeles','537-58-8889',110217),
('Los Angeles','808-68-4234',192836),
('Los Angeles','359-81-6735',209346),
('Los Angeles','731-80-2303',182186),
('Los Angeles','214-58-0842',125355),
('Chicago','456-79-9682',183698),
('Chicago','807-97-4784',194282),
('Chicago','981-16-3724',156083),
('Chicago','252-34-3054',226619),
('Chicago','613-28-9452',153366),
('Chicago','785-25-8628',205709),
('Chicago','451-26-7350',206085),
('Chicago','443-94-2401',120587),
('Chicago','696-26-8113',171185),
('Chicago','277-31-9760',211160),
('Dallas','537-88-7532',245231),
('Dallas','393-25-3503',238733),
('Dallas','612-17-0712',103152),
('Dallas','384-93-7285',228842),
('Dallas','745-10-7587',154749),
('Dallas','950-20-4045',102156),
('Dallas','477-48-7550',196533),
('Dallas','427-52-8597',238970),
('Dallas','891-19-0810',245204),
('Dallas','564-79-7612',196946),
('Boston','216-84-7134',128035),
('Boston','515-84-4073',249093),
('Boston','92-43-5775',205026),
('Boston','144-08-1092',198120),
('Boston','469-14-5012',174143),
('Boston','379-92-8313',166215),
('Boston','71-22-5132',105058),
('Boston','257-39-0324',107247),
('Boston','611-57-4279',118561),
('Boston','956-53-2865',232789),
('Denver','711-81-0072',240720),
('Denver','673-39-5028',159706),
('Denver','554-33-3980',232493),
('Denver','770-03-5304',203310),
('Denver','732-47-5077',123106),
('Denver','573-18-3567',149999),
('Denver','93-92-0334',162657),
('Denver','424-76-1468',116322),
('Denver','403-47-0063',246058),
('Denver','460-58-1833',198043),
('Miami','221-04-4153',130962),
('Miami','179-09-9839',227246),
('Miami','564-76-9437',144027),
('Miami','407-48-4081',138549),
('Miami','526-79-1840',208006),
('Miami','72-68-4977',170109),
('Miami','235-72-3903',191669),
('Miami','436-62-0474',161164),
('Miami','430-52-3914',162507),
('Miami','459-27-5541',238972),
('Phoenix','576-38-4531',238281),
('Phoenix','65-64-1278',197678),
('Phoenix','880-29-1997',159183),
('Phoenix','304-72-1881',194733),
('Phoenix','61-20-1046',221045),
('Phoenix','64-95-5514',105577),
('Phoenix','262-63-4021',186399),
('Phoenix','661-84-1023',234974),
('Phoenix','892-31-4821',115076),
('Phoenix','319-91-9463',239548),
('San Franciso','136-67-6873',148829),
('San Franciso','5-41-7374',114161),
('San Franciso','381-26-8852',232509),
('San Franciso','620-64-6243',112686),
('San Franciso','128-33-5550',208679),
('San Franciso','422-00-0156',107685),
('San Franciso','370-98-5607',133224),
('San Franciso','91-58-9543',218955),
('San Franciso','911-35-0448',187826),
('San Franciso','734-65-1268',223683),
('Atlanta','334-97-0585',240384),
('Atlanta','405-12-4222',124350),
('Atlanta','43-05-7567',233836),
('Atlanta','882-97-7996',134091),
('Atlanta','368-91-4292',173787),
('Atlanta','408-04-5921',140769),
('Atlanta','232-13-5280',206307),
('Atlanta','88-41-2584',118159),
('Atlanta','539-03-7548',116718),
('Atlanta','587-63-6935',174801)
)p(city, id, salary)
This produces the following result.
TRIMMEAN
----------------------
180297.866666667
(1 row(s) affected)
In this example we will calculate the mean for each city, trimming the top and bottom 10%.
SELECT city
,wct.TRIMMEAN(salary, .10) as TRIMMEAN
FROM (VALUES
('New York','429-00-6486',236503),
('New York','90-70-2526',224472),
('New York','87-85-0404',139802),
('New York','716-89-3089',185287),
('New York','159-78-5370',211900),
('New York','195-97-6820',186703),
('New York','95-49-2813',167451),
('New York','37-20-7422',149462),
('New York','44-48-0076',214708),
('New York','514-79-0041',226485),
('Los Angeles','526-34-4521',196402),
('Los Angeles','800-50-0868',205359),
('Los Angeles','41-34-3618',195679),
('Los Angeles','854-29-9398',131925),
('Los Angeles','673-30-3623',171091),
('Los Angeles','537-58-8889',110217),
('Los Angeles','808-68-4234',192836),
('Los Angeles','359-81-6735',209346),
('Los Angeles','731-80-2303',182186),
('Los Angeles','214-58-0842',125355),
('Chicago','456-79-9682',183698),
('Chicago','807-97-4784',194282),
('Chicago','981-16-3724',156083),
('Chicago','252-34-3054',226619),
('Chicago','613-28-9452',153366),
('Chicago','785-25-8628',205709),
('Chicago','451-26-7350',206085),
('Chicago','443-94-2401',120587),
('Chicago','696-26-8113',171185),
('Chicago','277-31-9760',211160),
('Dallas','537-88-7532',245231),
('Dallas','393-25-3503',238733),
('Dallas','612-17-0712',103152),
('Dallas','384-93-7285',228842),
('Dallas','745-10-7587',154749),
('Dallas','950-20-4045',102156),
('Dallas','477-48-7550',196533),
('Dallas','427-52-8597',238970),
('Dallas','891-19-0810',245204),
('Dallas','564-79-7612',196946),
('Boston','216-84-7134',128035),
('Boston','515-84-4073',249093),
('Boston','92-43-5775',205026),
('Boston','144-08-1092',198120),
('Boston','469-14-5012',174143),
('Boston','379-92-8313',166215),
('Boston','71-22-5132',105058),
('Boston','257-39-0324',107247),
('Boston','611-57-4279',118561),
('Boston','956-53-2865',232789),
('Denver','711-81-0072',240720),
('Denver','673-39-5028',159706),
('Denver','554-33-3980',232493),
('Denver','770-03-5304',203310),
('Denver','732-47-5077',123106),
('Denver','573-18-3567',149999),
('Denver','93-92-0334',162657),
('Denver','424-76-1468',116322),
('Denver','403-47-0063',246058),
('Denver','460-58-1833',198043),
('Miami','221-04-4153',130962),
('Miami','179-09-9839',227246),
('Miami','564-76-9437',144027),
('Miami','407-48-4081',138549),
('Miami','526-79-1840',208006),
('Miami','72-68-4977',170109),
('Miami','235-72-3903',191669),
('Miami','436-62-0474',161164),
('Miami','430-52-3914',162507),
('Miami','459-27-5541',238972),
('Phoenix','576-38-4531',238281),
('Phoenix','65-64-1278',197678),
('Phoenix','880-29-1997',159183),
('Phoenix','304-72-1881',194733),
('Phoenix','61-20-1046',221045),
('Phoenix','64-95-5514',105577),
('Phoenix','262-63-4021',186399),
('Phoenix','661-84-1023',234974),
('Phoenix','892-31-4821',115076),
('Phoenix','319-91-9463',239548),
('San Franciso','136-67-6873',148829),
('San Franciso','5-41-7374',114161),
('San Franciso','381-26-8852',232509),
('San Franciso','620-64-6243',112686),
('San Franciso','128-33-5550',208679),
('San Franciso','422-00-0156',107685),
('San Franciso','370-98-5607',133224),
('San Franciso','91-58-9543',218955),
('San Franciso','911-35-0448',187826),
('San Franciso','734-65-1268',223683),
('Atlanta','334-97-0585',240384),
('Atlanta','405-12-4222',124350),
('Atlanta','43-05-7567',233836),
('Atlanta','882-97-7996',134091),
('Atlanta','368-91-4292',173787),
('Atlanta','408-04-5921',140769),
('Atlanta','232-13-5280',206307),
('Atlanta','88-41-2584',118159),
('Atlanta','539-03-7548',116718),
('Atlanta','587-63-6935',174801)
)p(city, id, salary)
GROUP BY city
This produces the following result.
city TRIMMEAN
------------ ----------------------
Atlanta 166320.2
Boston 168428.7
Chicago 182877.4
Dallas 195051.6
Denver 183241.4
Los Angeles 172039.6
Miami 177321.1
New York 194277.3
Phoenix 189249.4
San Franciso 168823.7
(10 row(s) affected)
In this example we will calculate the mean for each city, trimming the top and bottom 10%, but only selecting those where the trimmed mean is greater than 180,000.
SELECT city
,wct.TRIMMEAN(salary, .10) as TRIMMEAN
FROM (VALUES
('New York','429-00-6486',236503),
('New York','90-70-2526',224472),
('New York','87-85-0404',139802),
('New York','716-89-3089',185287),
('New York','159-78-5370',211900),
('New York','195-97-6820',186703),
('New York','95-49-2813',167451),
('New York','37-20-7422',149462),
('New York','44-48-0076',214708),
('New York','514-79-0041',226485),
('Los Angeles','526-34-4521',196402),
('Los Angeles','800-50-0868',205359),
('Los Angeles','41-34-3618',195679),
('Los Angeles','854-29-9398',131925),
('Los Angeles','673-30-3623',171091),
('Los Angeles','537-58-8889',110217),
('Los Angeles','808-68-4234',192836),
('Los Angeles','359-81-6735',209346),
('Los Angeles','731-80-2303',182186),
('Los Angeles','214-58-0842',125355),
('Chicago','456-79-9682',183698),
('Chicago','807-97-4784',194282),
('Chicago','981-16-3724',156083),
('Chicago','252-34-3054',226619),
('Chicago','613-28-9452',153366),
('Chicago','785-25-8628',205709),
('Chicago','451-26-7350',206085),
('Chicago','443-94-2401',120587),
('Chicago','696-26-8113',171185),
('Chicago','277-31-9760',211160),
('Dallas','537-88-7532',245231),
('Dallas','393-25-3503',238733),
('Dallas','612-17-0712',103152),
('Dallas','384-93-7285',228842),
('Dallas','745-10-7587',154749),
('Dallas','950-20-4045',102156),
('Dallas','477-48-7550',196533),
('Dallas','427-52-8597',238970),
('Dallas','891-19-0810',245204),
('Dallas','564-79-7612',196946),
('Boston','216-84-7134',128035),
('Boston','515-84-4073',249093),
('Boston','92-43-5775',205026),
('Boston','144-08-1092',198120),
('Boston','469-14-5012',174143),
('Boston','379-92-8313',166215),
('Boston','71-22-5132',105058),
('Boston','257-39-0324',107247),
('Boston','611-57-4279',118561),
('Boston','956-53-2865',232789),
('Denver','711-81-0072',240720),
('Denver','673-39-5028',159706),
('Denver','554-33-3980',232493),
('Denver','770-03-5304',203310),
('Denver','732-47-5077',123106),
('Denver','573-18-3567',149999),
('Denver','93-92-0334',162657),
('Denver','424-76-1468',116322),
('Denver','403-47-0063',246058),
('Denver','460-58-1833',198043),
('Miami','221-04-4153',130962),
('Miami','179-09-9839',227246),
('Miami','564-76-9437',144027),
('Miami','407-48-4081',138549),
('Miami','526-79-1840',208006),
('Miami','72-68-4977',170109),
('Miami','235-72-3903',191669),
('Miami','436-62-0474',161164),
('Miami','430-52-3914',162507),
('Miami','459-27-5541',238972),
('Phoenix','576-38-4531',238281),
('Phoenix','65-64-1278',197678),
('Phoenix','880-29-1997',159183),
('Phoenix','304-72-1881',194733),
('Phoenix','61-20-1046',221045),
('Phoenix','64-95-5514',105577),
('Phoenix','262-63-4021',186399),
('Phoenix','661-84-1023',234974),
('Phoenix','892-31-4821',115076),
('Phoenix','319-91-9463',239548),
('San Franciso','136-67-6873',148829),
('San Franciso','5-41-7374',114161),
('San Franciso','381-26-8852',232509),
('San Franciso','620-64-6243',112686),
('San Franciso','128-33-5550',208679),
('San Franciso','422-00-0156',107685),
('San Franciso','370-98-5607',133224),
('San Franciso','91-58-9543',218955),
('San Franciso','911-35-0448',187826),
('San Franciso','734-65-1268',223683),
('Atlanta','334-97-0585',240384),
('Atlanta','405-12-4222',124350),
('Atlanta','43-05-7567',233836),
('Atlanta','882-97-7996',134091),
('Atlanta','368-91-4292',173787),
('Atlanta','408-04-5921',140769),
('Atlanta','232-13-5280',206307),
('Atlanta','88-41-2584',118159),
('Atlanta','539-03-7548',116718),
('Atlanta','587-63-6935',174801)
)p(city, id, salary)
GROUP BY city
HAVING wct.TRIMMEAN(salary, .10) > 180000
This produces the following result.
city TRIMMEAN
------------ ----------------------
Chicago 182877.4
Dallas 195051.6
Denver 183241.4
New York 194277.3
Phoenix 189249.4
(5 row(s) affected)
In this example we calculate the trimmed mean for a variety of data groupings, including one NULL value and a GROUP that only contains one member.
SELECT dsc
,wct.TRIMMEAN(x, .1) as TRIMMEAN
FROM (VALUES
('ABC', 15),('ABC',20),('ABC',35),('ABC',40),('ABC',50),
('DEF', 7),('DEF',10),('DEF',17),('DEF',20),('DEF',25),('DEF',70),
('GHI', 21),('DEF',28),('DEF',NULL),('DEF',38),('DEF',31),('DEF',52),
('JKL', 37)
) p(dsc, x)
GROUP BY dsc
This produces the following result.
dsc TRIMMEAN
---- ----------------------
ABC 32
DEF 29.8
GHI 21
JKL 37
(4 row(s) affected)