Reference · Statistics

stats.pstdev

stats.pstdev(list, num | null=) -> float

What it does

The population standard deviation of a list of numbers: the square root of stats.pvariance, as Python's statistics.pstdev. It is in the data's own units, where the variance is in their square. For a sample of a larger population use stats.stdev.

Examples

print(stats.pstdev([1, 2, 3, 4]))print(stats.pstdev([1.5, 2.5, 2.5, 2.75, 3.25, 4.75]))

1.1180339887498950.986893273527251

Edge cases

• One number is enough: its deviation is 0.0, and so is a constant list's.
• A second argument, a mean already known, is accepted, but the answer is the spread about the data's own mean whatever is given, as in Python before 3.11. Leave it out, or pass null.
• It is the square root of stats.pvariance exactly.

print(stats.pstdev([5]), stats.pstdev([7, 7, 7]))print(stats.pstdev([1, 2, 3, 4], 0), stats.pstdev([1, 2, 3, 4], null))print(stats.pstdev([1, 2, 3, 4]) == math.sqrt(stats.pvariance([1, 2, 3, 4])))

0.0 0.01.118033988749895 1.118033988749895true

Errors

No data is a runtime error, not an error value: an empty list or null stops the request. So does an item that is not a number.

print(stats.pstdev([]))

line 1: `stats.pstdev` requires at least one data point

Chaining

let xs = [2, 4, 4, 4, 5, 5, 7, 9]print(xs | stats.pstdev)print((xs | map((x) => (x - stats.mean(xs)) / stats.pstdev(xs))) == stats.zscore(xs))

2.0true

See also

stats.stdev, stats.pvariance, stats.zscore, math.sqrt

Edit this page on GitHub · every example's output was made by running it (tools/refcheck.mjs) · questions on Discord or r/quillo