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Weighted Average Calculator

Find the weighted mean of up to three values.

How it is calculated

A weighted average gives each value an importance, so items with bigger weights pull the result harder: average = (v₁w₁ + v₂w₂ + v₃w₃) ÷ (w₁ + w₂ + w₃). Here v is the value (a grade, price, score) and w is its weight (credits, quantity, percentage). The tool takes up to three value/weight pairs. A pair is skipped if either box is empty, so you can use only two pairs. The weights do not need to add up to 100; the division by the weight total takes care of scaling. If the total weight is zero there is no result. Rounded to two decimals.

Worked example

An exam is 30% of a course, homework 20% and a project 50%, with scores 80, 65 and 90. Multiply each score by its weight: 80 × 30 = 2,400; 65 × 20 = 1,300; 90 × 50 = 4,500. The sum is 8,200. Total weight is 30 + 20 + 50 = 100. Average: 8,200 ÷ 100 = 82.00. The plain average of the three scores would be 78.33, but the heavily weighted project lifts the weighted result.

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Common mistakes

  • Averaging the values plainly when the items count differently, such as courses with different credits.
  • Entering a value without its weight. The pair is ignored silently, so the result is based on fewer items than you think.
  • Putting the weights as percentages that do not add to 100 and assuming the result is wrong. It is still correct, because the division rescales.
  • Swapping value and weight columns, which gives a nonsensical average.

About this calculator

A weighted average multiplies each value by its own weight, sums those products, and divides by the total of the weights — Σ(value × weight) ÷ Σ(weight) — instead of treating every number as equally important the way a plain average does. This calculator handles up to three value/weight pairs at once.

It's the method behind a course grade where exams count more than homework, a portfolio's blended return when positions are different sizes, or an inventory's average cost when purchase batches arrived at different prices and quantities. Students checking a final grade, analysts blending returns, and shop owners costing stock all rely on this instead of a simple mean because ignoring the weights would give a misleading answer.

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