Computes the standard deviation across all column values of Integer or Decimal type.
The standard deviation of a set of values attempts to measure the spread in values around the mean and is used to measure confidence in statistical results. A standard deviation of zero means that all values are the same, and a small standard deviation means that the values are closely 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 variance from all possible values.
- Sample standard deviation computes from a subset or sample of all values.
- Since Designer Cloud Enterprise Edition has access to all available values, the computation for population standard deviation is used across the entire dataset.
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 0
.
The square of standard deviation is variance. See VAR Function.
For a version of this function computed over a rolling window of rows, see ROLLINGSTDEV Function.
Basic Usage
pivot value:STDEV(myRating) group: postal_code limit: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
parameter defines the maximum number of output columns.
Syntax and Arguments
pivot value:STDEV(function_col_ref) [group:group_col_ref] [limit:limit_count]
Argument | Required? | Data Type | Description |
---|---|---|---|
function_col_ref | Y | string | Name of column to which to apply the function |
For more information on the group
and limit
parameters, see Pivot Transform.
For more information on syntax standards, see Language Documentation Syntax Notes.
function_col_ref
Name of the column the values of which you want to calculate the variance. Column must contain Integer or Decimal values.
- Literal values are not supported as inputs.
- Multiple columns and wildcards are not supported.
Usage Notes:
Required? | Data Type | Example Value |
---|---|---|
Yes | String (column reference) | myValues |
Examples
Tip: For additional examples, see Common Tasks.
Source:
Students took a test and recorded the following scores. You want to perform some statistical analysis on them:
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), minimum, and maximum scores:
derive type:single value:AVERAGE(Score) as:'avgScore'
derive type:single value:MIN(Score) as:'minScore'
derive type:single value:MAX(Score) 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.
derive type:single value:VAR(Score)
derive type:single value:STDEV(Score)
For each score, you can now calculate the variation of each one from the average, using the following:
derive type:single value:((Score - avg_Score) / stdev_Score) as:'stDevs'
Now, you want to apply grades based on a formula:
Grade | standard deviations from avg (stDevs) |
---|---|
A | stDevs > 1 |
B | stDevs > 0.5 |
C | -1 <= stDevs <= 0.5 |
D | stDevs < -1 |
F | stDevs < -2 |
You can build the following transform using the IF
function to calculate grades.
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 Function.
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:
set col:stdev_Score value:NUMFORMAT(stdev_Score, '##.00')
set col:stDevs value:NUMFORMAT(stDevs, '##.00')
derive type:single value:MODE(Score) as:'modeScore'
Results:
Student | Score | modeScore | avgScore | minScore | maxScore | var_Score | stdev_Score | stDevs | Grade |
---|---|---|---|---|---|---|---|---|---|
Anna | 84 | 85 | 82 | 68 | 99 | 87.00000000000001 | 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 |
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