Crate use_statistics 

use-statistics

Small statistical summary helpers for `RustUse`.
Explicit mean, median, variance, and standard-deviation helpers over numeric slices.

Install

[dependencies]
use-statistics = "0.0.1"

Foundation

use-statistics provides a deliberately small descriptive-statistics surface over f64 slices. The crate currently exposes arithmetic mean, median, population variance, sample variance, and matching standard-deviation helpers, along with an explicit StatisticsError for empty inputs and too-small samples. The first slice stays simple and direct instead of introducing a full dataframe or distribution framework.

Central tendency mean and median cover the two common location summaries directly.

Dispersion population_variance, sample_variance, population_std_dev, and sample_std_dev keep the estimator choice explicit.

Explicit invalid-input handling StatisticsError distinguishes empty-input cases from undersized sample calculations.

Helper group	Primary items	Best fit
Central tendency	mean, median	Small apps and utilities that need direct descriptive summaries
Dispersion	population_variance, sample_variance, population_std_dev, sample_std_dev	Call sites that should remain explicit about population vs. sample summaries
Error handling	StatisticsError	Code that needs predictable handling for empty or undersized inputs

When to use directly

Choose use-statistics directly when statistical summaries or distributions are the only surface you need and you want to keep that concern narrower than the full facade.

Scenario	Use use-statistics directly?	Why
You need descriptive summaries over f64 slices	Yes	The current API already covers the common location and dispersion cases directly
You want explicit population-vs-sample summary functions	Yes	The function names keep estimator choice visible at the call site
You also need probability, calculus, or other math domains	Usually no	use-math can compose the concrete surfaces behind features

Scope

• The current surface is intentionally small and concrete.
• Helpers operate over borrowed f64 slices instead of introducing dataset wrapper types.
• Probability primitives and broader numerical analysis belong in adjacent focused crates.

Examples

Central tendency and population summaries

use use_statistics::{mean, median, population_std_dev, population_variance};

let values = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];

assert!((mean(&values)? - 5.0).abs() < 1.0e-12);
assert!((median(&values)? - 4.5).abs() < 1.0e-12);
assert!((population_variance(&values)? - 4.0).abs() < 1.0e-12);
assert!((population_std_dev(&values)? - 2.0).abs() < 1.0e-12);

Sample summaries

use use_statistics::{sample_std_dev, sample_variance};

let sample = [1.0, 2.0, 3.0, 4.0];

assert!((sample_variance(&sample)? - 1.666_666_666_666_666_7).abs() < 1.0e-12);
assert!((sample_std_dev(&sample)? - 1.290_994_448_735_805_6).abs() < 1.0e-12);

Status

use-statistics is a concrete pre-1.0 crate in the RustUse docs surface. The API remains intentionally small while adjacent probability and numeric-analysis crates continue to grow around it. Statistical utilities for RustUse.

Modules

prelude

Common ergonomic imports for use-statistics.

Enums

StatisticsError

Errors returned by statistics helpers when the input cannot support the requested summary.

Functions

mean

Returns the arithmetic mean of values.

median

Returns the median of values.

population_std_dev

Returns the population standard deviation of values.

population_variance

Returns the population variance of values.

sample_std_dev

Returns the sample standard deviation of values using Bessel’s correction.

sample_variance

Returns the sample variance of values using Bessel’s correction.