Date: Tue, 30 Nov 2021 01:25:04 +0000 (GMT) Message-ID: <262351074.83351.1638235504545@9c5033e110b2> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_83350_1011075810.1638235504545" ------=_Part_83350_1011075810.1638235504545 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html STDEV Function

# STDEV Function

Computes the standard deviation across all column values of= Integer or Decimal type.

The standard deviation of a set of values attempts to m= easure the spread in values around the mean and is used to measure confiden= ce in statistical results. A standard deviation of zero means that all valu= es are the same, and a small standard deviation means that the values are c= losely bunched together. A high value for standard deviation indicates that= the numbers are spread out widely. Standard deviation is always a positive= value.

Standard deviation comes in two flavors:

• Population standard deviation computes the vari= ance from all possible values.
• Sample standard deviation computes from a subse= t or sample of all values.
• Since Trifacta=C2=AE Self-Manag= ed Enterprise Edition has access to all available values, the comput= ation for population standard deviation is used across the entire dataset.<= /span>

If a row contains a missing or null value, it is not factored into= the calculation. If no numeric values are detected in the input colu= mn, the function returns `0` .

The square of standard deviation is variance. See VAR Function.

For a version of this function computed over a rolling window of rows, s= ee ROLLINGSTDEV Function.

## Basic Usage

=20

pivot value:STDEV(myRating) group: postal_code li= mit:1

Output: Generates a two-column table containing = the unique values from the `postal_code` column and the standard= deviation of the group of values from the `myRating` column for= the `postal_code` value. The `limit` p= arameter defines the maximum number of output columns.

## Syntax= and Arguments

=20

pivot value:STDEV(function_col_ref) [group:group_col_= ref] [limit:limit_count]

=20 =20 =20 =20 =20
Argument Required? Data Type Description
function_col_ref Y string Name of column to which to apply the funct= ion

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

### function_col_<= /span>ref

Name of the column the values of which you want to calculate the varianc= e. Column must contain Integer or Decimal values.

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

Usage Notes:

=20 =20 =20 =20
Required? Data Type Example Value
Yes String (column reference) `myValues`

## Examples

This example illustrates how you can apply statistical functions = to your dataset. Calculations include average (mean), max, min, standard de= viation, and variance.

Source:

Students took a test and recorded the following scores. You want to perf= orm some statistical analysis on them:

=20 =20 =20
Student Score
Anna 84
Ben 71
Caleb 76
Danielle 87
Evan 85
Faith 92
Gabe 85
Hannah 99
Ian 73
Jane 68

Transform:

You can use the following transforms to calculate the average (mean), mi= nimum, and maximum scores:

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derive type:single value:AVERAGE(Sco= re) as:'avgScore'

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derive type:single value:MIN(Score)<= span> as:'minScore'

=20

derive type:single value:MAX(Score)<= span> as:'maxScore'

To apply statistical functions to your data, you can use the ```VAR and STDEV functions, which can be used as the basis for = other statistical calculations.```

```=20 derive type:single value:VAR(Score)<= /span>=20 derive type:single value:STDEV(Score= ) For each score, you can now calculate the variation of each one from the= average, using the following:=20 derive type:single value:((Score - a= vg_Score) / stdev_Score) as:'stDevs' Now, you want to apply grades based on a formula: =20 =20 =20 Grade standard deviations from avg (stDevs) A stDevs > 1 B stDevs > 0.5 C -1 <=3D stDevs <=3D 0.5 D stDevs < -1 F stDevs < -2 You can build the following transform using the IF function= to calculate grades.=20 derive type:single value:IF((stDevs = > 1),'A',IF((stDevs < -2),'F',IF((stDevs < -1),'D',IF((stDevs >= 0.5),'B','C')))) For more information, see IF Funct= ion. ```

```To clean up the content, you might want to apply some formatting to the = score columns. The following reformats the stdev_Score and stDevs``` columns to display two decimal places:

=20

set col:stdev_Score value:NUMFORMAT(stdev_Score, = '##.00')

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set col:stDevs value:NUMFORMAT(stDevs, '##.00')

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derive type:single value:MODE(Score)= as:'modeScore'

Results:

=20 =20 =20 =20 =20 =20 =20 =20 =20 =20 =20
Student Score modeScore avgScore minScore maxScore var_Score stdev_Score stDevs Grade
Anna 84 85 82 68 99

87.00000000000001<= /p>

9.33 0.21 C
Ben 71 85 82 68 99 87.00000000000001 9.33 -1.18 D
Caleb 76 85 82 68 99 87.00000000000001 9.33 -0.64 C
Danielle 87 85 82 68 99 87.00000000000001 9.33 0.54 B
Evan 85 85 82 68 99 87.00000000000001 9.33 0.32 C
Faith 92 85 82 68 99 87.00000000000001 9.33 1.07 A
Gabe 85 85 82 68 99 87.00000000000001 9.33 0.32 C
Hannah 99 85 82 68 99 87.00000000000001 9.33 1.82 A
Ian 73 85 82 68 99 87.00000000000001 9.33 -0.96 C
Jane 68 85 82 68 99 87.00000000000001 9.33 -1.50 D
=20

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