Computes the standard deviation across all column values of Int=
eger or Decimal type. The **standard deviation** of a set of values attempts to measure t=
he spread in values around the mean and is used to measure confidence in st=
atistical results. A standard deviation of zero means that all values are t=
he same, and a small standard deviation means that the values are closely b=
unched together. A high value for standard deviation indicates that the num=
bers are spread out widely. Standard deviation is always a positive value.<=
/p>

Standard deviation comes in two fl= avors:

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=
column, the function returns 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 Functi=
on. pivot value:STDEV(myRating) group: postal_code li=
mit:1 pivot value:STDEV(function_col_ref) [group:group_col_=
ref] [limit:limit_count] For more information on the For more information on syntax standards, see Language Documentation Syntax Note=
s. Name of the column the values of which you want to calculate the varianc=
e. Column must contain Integer or Decimal values. This example illustrates how you can apply statistical functions t=
o your dataset. Calculations include average (mean), max, min, standard dev=
iation, and variance. Students took a test and recorded the following scores. You want to perf=
orm some statistical analysis on them: You can use the following transforms to calculate the average (mean), mi=
nimum, and maximum scores: derive type:single value:AVERAGE(Sco=
re) as:'avgScore' derive type:single value:MIN(Score)<=
span> as:'minScore' derive type:single value:MAX(Score)<=
span> as:'maxScore' derive type:single value:VAR(Score)<=
/span> derive type:single value:STDEV(Score=
) derive type:single value:((Score - a=
vg_Score) / stdev_Score) as:'stDevs' You can build the following transform using the derive type:single value:IF((stDevs =
> 1),'A',IF((stDevs < -2),'F',IF((stDevs < -1),'D',IF((stDevs >=
0.5),'B','C')))) To clean up the content, you might want to apply some formatting to=
the score columns. The following reformats the set col:stdev_Score value:NUMFORMAT(stdev_Score, =
'##.00') set col:stDevs value:NUMFORMAT(stDevs, '##.00') derive type:single value:MODE(Score)=
as:'modeScore' 87.00000000000001<=
/p>

**Population standard devia=
tion** computes the variance from all possible values. **Sample standard deviation=
** computes from a subset or sample of all values. `0`

.## Basic Usage

=20
**Output:** Gene=
rates 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`

valu=
e. The `limit parameter defines the maximum number of output columns.`

```
```

` `

```
```

## Syntax=
and Arguments

=20

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

and ```
limit=
```

parameters, see Pivot Transform.## function_col_<=
/span>ref

**Usage Notes:**

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

## Examples

**Tip:** For additional examples, see Common Tasks.**Source:**

Student
Score
Anna
84
Ben
71
Caleb
76
Danielle
87
Evan
85
Faith
92
Gabe
85
Hannah
99
Ian
73
Jane
68
**Transform:**`VAR`

and
`STDEV`

functions, which can be used as the basis for other stat=
istical calculations. =20

Grade
standard devi=
ations from avg (stDevs)
A
stDevs > 1
B
stDevs > 0.5
C
-1 <=3D stDevs <=3D 0.5
D
stDevs < -1
F
stDevs < -2
`IF`

&nbs=
p;function to calculate grades. `stdev_Score`

an=
d `stDevs`

columns to display two decimal places: **Results:**

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