Weighted Average Calculator
Calculate the weighted average of up to 8 values. See total weight, each value's contribution %, weighted standard deviation, and sensitivity analysis.
Weighted Average
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Total Weight —
Contribution of Value 1 —
Contribution of Value 2 —
Contribution of Value 3 —
Extended More scenarios, charts & detailed breakdown ▾
Weighted Average
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Total Weight —
Professional Full parameters & maximum detail ▾
Core Results
Weighted Average —
Total Weight —
Weight Analysis
Normalized Weights (to 100%) —
Each Value Contribution (%) —
Statistical Depth
Weighted Std Deviation —
Simple Mean (comparison) —
Sensitivity: +10% on heaviest value —
How to Use This Calculator
Enter up to 3 values and their corresponding weights. The calculator instantly shows the weighted average, total weight, and each value's contribution. Use the 5 Values tab for more data points. Use Grade Weighted for assignments with different point values. The Professional tab supports 8 values with normalized weights and sensitivity analysis.
Formula
Weighted Average = Σ(value × weight) / Σ(weight)
Contribution % = weight / total weight × 100
Example
Values: 85, 72, 90 with weights 3, 2, 5 → Total weight = 10 → Weighted avg = (85×3 + 72×2 + 90×5) / 10 = 84.9
Frequently Asked Questions
- A weighted average multiplies each value by its relative importance (weight) and divides the sum by the total weight. It differs from a simple average where all values count equally.
- A simple average treats all values equally. A weighted average assigns more importance to values with higher weights, shifting the result toward heavily-weighted values.
- Each value's contribution % shows what share of the weighted average that value's weight represents. A weight of 3 out of a total weight of 10 contributes 30%.
- Use the Grade Weighted tab. Enter your score and the total points for each assignment. The calculator sums your earned points and divides by total possible points.
- Weighted standard deviation measures how spread out the values are, accounting for their weights. Larger weights pull the deviation toward those values.