Mathematics · Statistics

Weighted Mean Calculator

Calculate the weighted mean of three values when observations have different importance or frequency.

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
Weighted mean80
Sum of weights4
Weighted sum320

Calculation steps

  1. Weighted sum = 70×1 + 80×2 + 90×1 = 320.
  2. Sum of weights = 4.
  3. Weighted mean = 320 ÷ 4 = 80.

Understand Weighted mean

One idea, three depths

Choose how deeply to explain Weighted mean

Calculate the weighted mean of three values when observations have different importance or frequency.

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

Imagine using Weighted mean to answer this question: calculate the weighted mean of three values when observations have different importance or frequency? Enter Value 1, Weight 1, Value 2, and 3 other inputs; the calculator shows Weighted mean. For example: Values 70, 80 and 90 with weights 1, 2 and 1 have weighted mean 80. The answer tells you Weighted mean.

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

Each value contributes in proportion to its weight, so larger weights exert more influence on the mean. The rule is Weighted mean = Σ(wx) ÷ Σw. Its input values are Value 1, Weight 1, Value 2, Weight 2, Value 3, Weight 3, and the main result is Weighted mean. For example: Values 70, 80 and 90 with weights 1, 2 and 1 have weighted mean 80.

CollegeExplain it at college levelState the model precisely

This calculator evaluates the stated weighted mean relation over the valid real-number domain stated below. The implemented relation is Weighted mean = Σ(wx) ÷ Σw, evaluated from Value 1, Weight 1, Value 2, Weight 2, Value 3, Weight 3 to produce Weighted mean. Each value contributes in proportion to its weight, so larger weights exert more influence on the mean. Divide by the sum of weights, not by the number of entered values.

Inputs and valid domain

  • Value 1 must be a finite real number.
  • Weight 1 must be a finite real number, at least 0.
  • Value 2 must be a finite real number.
  • Weight 2 must be a finite real number, at least 0.
  • Value 3 must be a finite real number.
  • Weight 3 must be a finite real number, at least 0.

Important boundary: Divide by the sum of weights, not by the number of entered values.

The formula

Weighted mean = Σ(wx) ÷ Σw

How the calculator works through it

It substitutes Value 1, Weight 1, Value 2, Weight 2, Value 3, Weight 3 into the formula and exposes every numerical step above. The main output is Weighted mean, accompanied by Sum of weights, Weighted sum.

Read the result correctly

The Weighted mean is the direct answer to “calculate the weighted mean of three values when observations have different importance or frequency.” Read it with the units shown beside the inputs; a sign, angle, percentage or rate changes what the number means.

A worked check

Values 70, 80 and 90 with weights 1, 2 and 1 have weighted mean 80.

Where this model stops being reliable

Divide by the sum of weights, not by the number of entered values.

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 Weighted mean works. They never block the calculator, and “optional” means useful context rather than a hidden requirement.

Hard requirements

  • Reading formulas and substituting values

    Weighted mean uses Weighted mean = Σ(wx) ÷ Σw. 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 Weighted mean 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 Weighted mean 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 Value 1, Weight 1, Value 2, Weight 2, Value 3, Weight 3.
  2. Evaluate the principal relationship: Weighted mean = Σ(wx) ÷ Σw.
  3. Return Weighted mean and check the domain conditions described above.
Python
            from math import *

def weighted_mean(v1, a, v2, b, v3, c) -> float:
    return ((((v1 * a) + (v2 * b)) + (v3 * c)) / ((a + b) + c))

assert abs(weighted_mean(70, 1, 80, 2, 90, 1) - 80) < 1e-6 * max(1.0, abs(80))
          
Current calculator valuesUpdates when you change an input above.
              
            
C
            #include <assert.h>
#include <math.h>

double weighted_mean(double v1, double a, double v2, double b, double v3, double c) {
    return ((((v1 * a) + (v2 * b)) + (v3 * c)) / ((a + b) + c));
}

int main(void) {
    const double expected = 80;
    const double actual = weighted_mean(70, 1, 80, 2, 90, 1);
    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 weighted_mean(double v1, double a, double v2, double b, double v3, double c) {
    return ((((v1 * a) + (v2 * b)) + (v3 * c)) / ((a + b) + c));
}

int main() {
    constexpr double expected = 80;
    const double actual = weighted_mean(70, 1, 80, 2, 90, 1);
    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 weighted_mean(double v1, double a, double v2, double b, double v3, double c)
; Linux x86-64 NASM · System V ABI · first eight doubles in xmm0–xmm7
global weighted_mean
section .text

weighted_mean:
    push rbp
    mov rbp, rsp
    sub rsp, 112
    movsd [rbp-8], xmm0
    movsd [rbp-16], xmm1
    movsd [rbp-24], xmm2
    movsd [rbp-32], xmm3
    movsd [rbp-40], xmm4
    movsd [rbp-48], xmm5
    movsd xmm0, [rbp-8]
    mulsd xmm0, [rbp-16]
    movsd [rbp-80], xmm0
    movsd xmm0, [rbp-24]
    mulsd xmm0, [rbp-32]
    movsd [rbp-88], xmm0
    movsd xmm0, [rbp-80]
    addsd xmm0, [rbp-88]
    movsd [rbp-72], xmm0
    movsd xmm0, [rbp-40]
    mulsd xmm0, [rbp-48]
    movsd [rbp-96], xmm0
    movsd xmm0, [rbp-72]
    addsd xmm0, [rbp-96]
    movsd [rbp-64], xmm0
    movsd xmm0, [rbp-16]
    addsd xmm0, [rbp-32]
    movsd [rbp-112], xmm0
    movsd xmm0, [rbp-112]
    addsd xmm0, [rbp-48]
    movsd [rbp-104], xmm0
    movsd xmm0, [rbp-64]
    divsd xmm0, [rbp-104]
    movsd [rbp-56], xmm0
    movsd xmm0, [rbp-56]
    leave
    ret
          
Current calculator valuesUpdates when you change an input above.
              
            
MATLAB
            function result = weighted_mean(v1, a, v2, b, v3, c)
    result = ((((v1 * a) + (v2 * b)) + (v3 * c)) / ((a + b) + c));
end
          
Current calculator valuesUpdates when you change an input above.
              
            
Wolfram Language
            ClearAll[mwCalculate];
mwCalculate[v1_, a_, v2_, b_, v3_, c_] := ((((v1 * a) + (v2 * b)) + (v3 * c)) / ((a + b) + c));
          
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). Weighted Mean Calculator. MW SysArc Tools. https://math.mwsysarc.com/statistics/weighted-mean-calculator

MLA 9

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

Chicago 17

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

Harvard

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

BibTeX and RIS records

BibTeX

@misc{mwsysarc_weighted_mean_2026,
  author = {{MW SysArc}},
  title = {Weighted Mean Calculator},
  howpublished = {MW SysArc Tools},
  year = {2026},
  url = {https://math.mwsysarc.com/statistics/weighted-mean-calculator},
  note = {Published July 21, 2026; accessed August 31, 2026}
}

RIS

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

Clear answers

Frequently asked questions

What does the Weighted mean do?

Calculate the weighted mean of three values when observations have different importance or frequency.

How does the Weighted mean work?

The calculator applies Weighted mean = Σ(wx) ÷ Σw. Each value contributes in proportion to its weight, so larger weights exert more influence on the mean.

What can I learn from the Weighted mean?

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 .

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