fintech-algorithms
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Measurement Error, Resolution, Accuracy, and Precision

Install and import#

bash
npm install fintech-algorithms
ts
import { measurementErrorResolutionAccuracyAndPrecision } from "fintech-algorithms/foundations/data-variables-samples-and-measurement/measurement-error-resolution-accuracy-and-precision";

Signature#

measurementErrorResolutionAccuracyAndPrecision(input)

Compares repeated measurements against a known reference to separate accuracy from precision, and reads the instrument's resolution off the spacing of the values it reports.

Parameters#

NameTypeNotes
inputD00InputA plain object. Every F03 topic first reads rows, which must be a non-empty array of row objects, and derives the sorted union of every key seen across them before any per-topic branch runs, even though this topic does not use them. The calculation itself reads measurements, a non-empty array of finite numbers, and referenceValue, the true value they are aimed at.

Returns#

{ bias: number; mae: number; resolution: number; precisionStd: number }

bias is the mean signed error against referenceValue and mae is the mean absolute error. resolution is the smallest gap between consecutive distinct measurements. precisionStd is the population standard deviation of the measurements, dividing by n rather than n-1.

Errors#

  • When input is not a plain object — throws TypeError
  • When rows is missing, empty, or not an array — throws RangeError
  • When measurements is missing, empty, not an array, or contains a non-finite number — throws RangeError

Complexity: time O(r * c + m log m), space O(r * c + m).

Worked example#

verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

Input#

input
{
  "rows": [
    {
      "entity": "A",
      "timestamp": "2025-01-01T00:00:00Z",
      "value": 10,
      "rating": "low"
    },
    {
      "entity": "A",
      "timestamp": "2025-01-02T00:00:00Z",
      "value": null,
      "rating": "medium",
      "censored": true
    },
    {
      "entity": "B",
      "timestamp": "2025-01-01T00:00:00Z",
      "value": 12,
      "rating": "high"
    }
  ],
  "ordinalColumns": ["rating"],
  "populationSize": 100,
  "frameSize": 80,
  "keyColumns": ["entity", "timestamp"],
  "truncationRule": "values below 5 excluded",
  "measurements": [9.9, 10, 10.1, 10],
  "referenceValue": 10,
  "vintages": [
    {
      "availableAt": "2025-02-01T00:00:00Z",
      "value": 100
    },
    {
      "availableAt": "2025-03-01T00:00:00Z",
      "value": 102
    },
    {
      "availableAt": "2025-04-01T00:00:00Z",
      "value": 101
    }
  ],
  "asOf": "2025-03-15T00:00:00Z",
  "provenance": {
    "source": "teaching.csv",
    "owner": "Fintech Builder",
    "license": "CC-BY-4.0",
    "retrievedAt": "2026-08-10",
    "transformations": ["parse", "validate"]
  }
}

Call#

measurementErrorResolutionAccuracyAndPrecision(input)

Returns#

object with 2 fields: bias, mae

{
  "bias": 0,
  "mae": 0.04999999999999982
}

Diagrams#

Measurement Error, Resolution, Accuracy, and Precision — article hero
Measurement Error, Resolution, Accuracy, and Precision — concept anatomy
Measurement Error, Resolution, Accuracy, and Precision — mistake contrast
Measurement Error, Resolution, Accuracy, and Precision — teaching map

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

  • Accuracy
  • Terminology
  • Evidence boundary

The rest of the Data, Variables, Samples, and Measurement family#