Mathematics · Statistics

Mean Forecast Error Calculator

Calculate mean forecast error from sum of signed forecast errors and forecast observation count.

Runs locally
Your numbers

Inputs and results stay in this browser. Change one value at a time to explore the relationship.

Your inputCalculatedPassed forward in chains
mean forecast error-0.15

Calculation steps

  1. Use c=a/b with sum of signed forecast errors=-18 and forecast observation count=120.
  2. mean forecast error=-0.15.

Understand Mean Forecast Error

One idea, three depths

Choose how deeply to explain Mean Forecast Error

Calculate mean forecast error from sum of signed forecast errors and forecast observation count.

Age 5Explain it to a 5-year-oldStart with a picture

Imagine using Mean Forecast Error to answer this question: calculate mean forecast error from sum of signed forecast errors and forecast observation count? Enter sum of signed forecast errors and forecast observation count; the calculator shows mean forecast error. For example: sum of signed forecast errors=-18 and forecast observation count=120 produce mean forecast error=-0.15. The answer tells you mean forecast error.

Age 15Explain it to a 15-year-oldConnect it to the formula

Mean forecast error averages signed actual-minus-forecast errors to measure systematic bias. This page evaluates the relationship directly. The rule is c=a/b. Its input values are sum of signed forecast errors, forecast observation count, and the main result is mean forecast error. For example: sum of signed forecast errors=-18 and forecast observation count=120 produce mean forecast error=-0.15.

CollegeExplain it at college levelState the model precisely

This calculator evaluates the stated mean forecast error relation over the valid real-number domain stated below. The implemented relation is c=a/b, evaluated from sum of signed forecast errors, forecast observation count to produce mean forecast error. Mean forecast error averages signed actual-minus-forecast errors to measure systematic bias. This page evaluates the relationship directly. State the error sign convention because reversing it changes the reported bias sign.

Inputs and valid domain

  • sum of signed forecast errors must be a finite real number.
  • forecast observation count must be a finite real number.

Important boundary: State the error sign convention because reversing it changes the reported bias sign.

The formula

c=a/b

How the calculator works through it

It substitutes sum of signed forecast errors, forecast observation count into the formula and exposes every numerical step above. The main output is mean forecast error.

Read the result correctly

The mean forecast error is the direct answer to “calculate mean forecast error from sum of signed forecast errors and forecast observation count.” Read it with the units shown beside the inputs; a sign, angle, percentage or rate changes what the number means.

A worked check

sum of signed forecast errors=-18 and forecast observation count=120 produce mean forecast error=-0.15.

Where this model stops being reliable

State the error sign convention because reversing it changes the reported bias sign.

Learn it by changing one value

Begin with the worked example, then change one value while keeping the others fixed. Compare the new result and calculation steps to identify which part of the formula changed.

Dictionary terms behind this calculator

Before studying the codeWhat you should know firstUse the calculator immediately, or check the foundations before reading the implementation.

These foundations help you understand why Mean Forecast Error works. They never block the calculator, and “optional” means useful context rather than a hidden requirement.

Hard requirements

  • Reading formulas and substituting values

    Mean Forecast Error uses c=a/b. You need to recognise what each side represents before substituting the stated inputs or rearranging the relationship.

    Review this foundation about 4 min

Strong support

  • Averages and representative values

    Representative values help you judge what the Mean Forecast Error inputs summarise and what the result can legitimately describe.

    Review this foundation about 5 min

Optional enrichment

  • Spread and measurement variation

    Variation is not always part of the Mean Forecast Error formula, but it helps you judge how stable a reported result may be.

    Review this foundation about 6 min
Learn the missing foundationsI already know these — show the code

Mathematics → algorithm → program

Implement this calculation in code

These are direct reference implementations of the calculator's principal relationship and first output. They run locally and include a small known-answer check where the language supports it.

Algorithm

  1. Read sum of signed forecast errors, forecast observation count.
  2. Evaluate the principal relationship: c=a/b.
  3. Return mean forecast error and check the domain conditions described above.
Python
            from math import *

def mean_forecast_error_calculator(a, b) -> float:
    return (a / b)

assert abs(mean_forecast_error_calculator(-18, 120) - -0.15) < 1e-6 * max(1.0, abs(-0.15))
          
Current calculator valuesUpdates when you change an input above.
              
            
C
            #include <assert.h>
#include <math.h>

double mean_forecast_error_calculator(double a, double b) {
    return (a / b);
}

int main(void) {
    const double expected = -0.15;
    const double actual = mean_forecast_error_calculator(-18, 120);
    assert(fabs(actual - expected) < 1e-6 * fmax(1.0, fabs(expected)));
}
          
Current calculator valuesUpdates when you change an input above.
              
            
C++
            #include <cassert>
#include <cmath>
#include <numbers>

double mean_forecast_error_calculator(double a, double b) {
    return (a / b);
}

int main() {
    constexpr double expected = -0.15;
    const double actual = mean_forecast_error_calculator(-18, 120);
    assert(std::fabs(actual - expected) < 1e-6 * std::fmax(1.0, std::fabs(expected)));
}
          
Current calculator valuesUpdates when you change an input above.
              
            
Linux x86-64 assembly

x86-64 NASM · System V ABI · Linux · SSE2 with libm where required

            ; double mean_forecast_error_calculator(double a, double b)
; Linux x86-64 NASM · System V ABI · first eight doubles in xmm0–xmm7
global mean_forecast_error_calculator
section .text

mean_forecast_error_calculator:
    push rbp
    mov rbp, rsp
    sub rsp, 32
    movsd [rbp-8], xmm0
    movsd [rbp-16], xmm1
    movsd xmm0, [rbp-8]
    divsd xmm0, [rbp-16]
    movsd [rbp-24], xmm0
    movsd xmm0, [rbp-24]
    leave
    ret
          
Current calculator valuesUpdates when you change an input above.
              
            
MATLAB
            function result = mean_forecast_error_calculator(a, b)
    result = (a / b);
end
          
Current calculator valuesUpdates when you change an input above.
              
            
Wolfram Language
            ClearAll[mwCalculate];
mwCalculate[a_, b_] := (a / b);
          
Current calculator valuesUpdates when you change an input above.
              
            

Continue in mathematical software

The downloaded file includes your current inputs and first calculated result. It is created locally.

Floating-point answers can differ slightly by language, compiler and processor. Compare within a suitable tolerance rather than assuming every decimal representation will be identical.

Supporting sourcesAcademic referencesPrimary standards, textbooks and complete citations

Standards, reading and academic references

Use the calculator as the worked interaction, then consult the primary standards and academic textbooks listed below. MW SysArc links to the original sources; the explanation on this page is original and does not reproduce them.

Introductory Statistics 2e

Read the free OpenStax statistics textbook
Cite this book
APA 7
Illowsky, B., & Dean, S. (2023). Introductory statistics 2e. OpenStax. https://openstax.org/books/introductory-statistics-2e/pages/1-introduction
MLA 9
Illowsky, Barbara, and Susan Dean. Introductory Statistics 2e. OpenStax, 2023, https://openstax.org/books/introductory-statistics-2e/pages/1-introduction.
Chicago author-date
Illowsky, Barbara, and Susan Dean. 2023. Introductory Statistics 2e. Houston, TX: OpenStax. https://openstax.org/books/introductory-statistics-2e/pages/1-introduction.

OpenStax entries are free to read online. Follow the licence shown on each linked source before redistributing or adapting its content.

Reuse the page responsiblyCite this pageAPA, MLA, Chicago, Harvard, BibTeX and RIS

These formats cite this calculator page itself. They are separate from the academic references above, which support the mathematical method and terminology.

APA 7

MW SysArc. (2026, July 21). Mean Forecast Error Calculator. MW SysArc Tools. https://math.mwsysarc.com/statistics/mean-forecast-error-calculator

MLA 9

MW SysArc. “Mean Forecast Error Calculator.” MW SysArc Tools, 21 July 2026, https://math.mwsysarc.com/statistics/mean-forecast-error-calculator. Accessed 31 Aug. 2026.

Chicago 17

MW SysArc. “Mean Forecast Error Calculator.” MW SysArc Tools. Published July 21, 2026. Accessed August 31, 2026. https://math.mwsysarc.com/statistics/mean-forecast-error-calculator.

Harvard

MW SysArc (2026) ‘Mean Forecast Error Calculator’, MW SysArc Tools. Published 21 July 2026. Available at: https://math.mwsysarc.com/statistics/mean-forecast-error-calculator (Accessed: 31 August 2026).

BibTeX and RIS records

BibTeX

@misc{mwsysarc_mean_forecast_error_calculator_2026,
  author = {{MW SysArc}},
  title = {Mean Forecast Error Calculator},
  howpublished = {MW SysArc Tools},
  year = {2026},
  url = {https://math.mwsysarc.com/statistics/mean-forecast-error-calculator},
  note = {Published July 21, 2026; accessed August 31, 2026}
}

RIS

TY  - ELEC
AU  - MW SysArc
TI  - Mean Forecast Error Calculator
T2  - MW SysArc Tools
PY  - 2026
DA  - 2026-07-21
Y2  - 2026-08-31
UR  - https://math.mwsysarc.com/statistics/mean-forecast-error-calculator
N1  - Published July 21, 2026
ER  -

Clear answers

Frequently asked questions

What does the Mean Forecast Error do?

Calculate mean forecast error from sum of signed forecast errors and forecast observation count.

How does the Mean Forecast Error work?

The calculator applies c=a/b. Mean forecast error averages signed actual-minus-forecast errors to measure systematic bias. This page evaluates the relationship directly.

What can I learn from the Mean Forecast Error?

It connects the mathematical rule to your chosen numbers and shows each calculation step. Change one input at a time to see how the result responds.

Does MW SysArc receive or store what I enter?

No. The calculation runs locally in your browser. MW SysArc does not receive or store your calculation inputs.

How should I use the result?

Use the steps to understand the method, then verify important school or professional work using the notation and rounding rules required in your setting.

Last reviewed . Calculations tested .

MW SysArc Certified