Date: Mon, 25 Oct 2021 11:39:41 +0000 (GMT) Message-ID: <842216914.55474.1635161981797@9c5033e110b2> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_55473_479886102.1635161981797" ------=_Part_55473_479886102.1635161981797 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html VARSAMP Function

# VARSAMP Function

Computes the variance among all values in a column=20 using the sample statistical method. Input column can be of In= teger or Decimal. If no numeric values are detected in the input colum= n, the function returns  `0`

The variance of a set of values attempts to measur= e the spread in values around the mean. A variance of zero means that all v= alues are the same, and a small variance means that the values are closely = bunched together. A high value for variance indicates that the numbers are = spread out widely. Variance is always a positive value.

If a row contains a missing or null value, it is not factored into the c= alculation.

NOTE: This function applies to a sample of the entire p= opulation. More information is below.

Terms...
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Relevant terms:

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TermDescription
PopulationPopulation statistical functions are computed fr= om all possible values. See https://en.wikip= edia.org/wiki/Statistical_population.
Sample=20
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Sample-based statistical functions are computed from a subset or sample = of all values. See https://en.wikipedia.org/w= iki/Sampling_(statistics).

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These function names include `SAMP` in their name.

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NOTE: Statistical sampling has no relationship to the = samples taken within the product. When statistical functions are computed d= uring job execution, they are applied across the entire dataset. Sample met= hod calculations are computed at that time.

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• This function is calculated across a sample of all values.

• For more information on a population version of this function, see = ;VAR Function.

In the following computation, the sample method computes variances with = N - 1 as the divisor.

Var(X) =3D [Sum ((X - mean(X))2)] / (Count(X) - 1)

The square root of variance is standard deviation, which is used to meas= ure variance under the assumption of a bell curve distribution. See STDEV Function.

For a version of this function co= mputed over a rolling window of rows, see ROLLINGVAR Function.

Wrangle vs. SQL: This function is part of Wrangle , a proprietary data transformation language.= Wrangle is not SQL. For more information, se= e Wrangle Language.

## Basic Usage

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varsamp(myRating)

Ou= tput: Returns the variance of the group of values from the&nb= sp;`myRating` column using the = sample method of calculation.

## Synt= ax and Arguments

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varsamp(col_ref) [group:group= _col_ref] [limit:limit_count]

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Argument Required? Data Type Description
function_col_ref Y string Name of column to which to apply the funct= ion

For more information on the `group` and ```limit= ``` parameters, see Pivot Transform.

For more information on syntax standards, see Language Documentation Syntax Notes= .

### col_ref

Name of the column whose values you wish to use in the calculation. Colu= mn must be a numeric (Integer or Decimal) type.

• Literal values are not supported as inputs.
• Multiple columns and wildcards are not supported.

Usage Notes:

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Required? Data Type Example Value
Yes String (column reference) `myValues`

## Examples

This example shows some of the statistical functions that use the= sample method of computation. These include:

Source:

Students took tests on three consecutive Saturdays:

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Student Date Score
Andrew 11/9/19 81
Bella 11/9/19 84
Christina 11/9/19 79
David 11/9/19 64
Ellen 11/9/19 61
Fred 11/9/19 63
Andrew 11/16/19 73
Bella 11/16/19 88
Christina 11/16/19 78
David 11/16/19 67
Ellen 11/16/19 87
Fred 11/16/19 90
Andrew 11/23/19 76
Bella 11/23/19 93
Christina 11/23/19 81
David 11/23/19 97
Ellen 11/23/19 97
Fred 11/23/19 91

Transformation:

You can use the following transformations to calculate standard deviatio= n and variance across all dates using the sample method. Each computation h= as been rounded to three digits.

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Transformation Name <= code>New formula `Single row formula` `round(stdevsamp(Score), 3)` `'stdevSamp'`
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Transformation Name <= code>New formula `Single row formula` `round(varsamp(Score), 3)` `'varSamp'`
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You can use the following to limit the previous statistical computations= to the last two Saturdays of testing:

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Transformation Name <= code>New formula `Single row formula` ```round(stdevsampif(Score, Date !=3D '11\/9\= /2019'), 3)``` `'stdevSampIf'`
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Transformation Name <= code>New formula `Single row formula` ```round(varsampif(Score, Date !=3D '11\/9\/2= 019'), 3)``` `'varSampIf'`
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Results:

Student Date Score varSampIf stdevSampIf varSamp stdevSamp
Andrew 11/9/19 81 94.515 9.722 131.673 11.475
Bella 11/9/19 84 94.515 9.722 131.673 11.475
Christina 11/9/19 79 94.515 9.722 131.673 11.475
David 11/9/19 64 94.515 9.722 131.673 11.475
Ellen 11/9/19 61 94.515 9.722 131.673 11.475
Fred 11/9/19 63 94.515 9.722 131.673 11.475
Andrew 11/16/19 73 94.515 9.722 131.673 11.475
Bella 11/16/19 88 94.515 9.722 131.673 11.475
Christina 11/16/19 78 94.515 9.722 131.673 11.475
David 11/16/19 67 94.515 9.722 131.673 11.475
Ellen 11/16/19 87 94.515 9.722 131.673 11.475
Fred 11/16/19 90 94.515 9.722 131.673 11.475
Andrew 11/23/19 76 94.515 9.722 131.673 11.475
Bella 11/23/19 93 94.515 9.722 131.673 11.475
Christina 11/23/19 81 94.515 9.722 131.673 11.475
David 11/23/19 97 94.515 9.722 131.673 11.475
Ellen 11/23/19 97 94.515 9.722 131.673 11.475
Fred 11/23/19 91 94.515 9.722 131.673 11.475
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