Weighted Average Calculator
Calculate weighted average (weighted mean) with different weights and values. Perfect for GPA calculations, test scores, portfolio analysis, and statistical calculations where values have different importance.
Calculate Weighted Average
Example: 85,3 means value=85 with weight=3
Common Weighted Average Examples
Click on these links to see instant calculations with common scenarios:
Weighted Average Calculations
A weighted average is a mean calculation where each value is multiplied by a weight that reflects its relative importance or frequency in the dataset.
Weighted Average Formula
Where: Σ = sum of all, value = data point, weight = importance factor
Example: (85×3 + 90×4 + 78×2) / (3+4+2) = 759/9 = 84.33
Common Weighted Average Examples
| Scenario | Values | Weights | Weighted Average |
|---|---|---|---|
| GPA Calculation | 85, 90, 78 | 3, 4, 2 credits | 84.33 |
| Test Scores | 80, 90, 95 | 20%, 30%, 50% | 89.5 |
| Portfolio Returns | 5%, 8%, 12% | $1000, $2000, $3000 | 9.17% |
| Course Grades | 75, 85, 95 | 25%, 35%, 40% | 86.5 |
| Survey Results | 4.2, 4.5, 3.8 | 100, 150, 75 responses | 4.28 |
- Education: Calculate GPA, course grades, and weighted test scores
- Finance: Portfolio returns, weighted cost of capital, and investment analysis
- Statistics: Survey data analysis and demographic weighting
- Business: Performance metrics, KPI calculations, and quality scores
- Research: Meta-analysis, data aggregation, and statistical modeling
Frequently Asked Questions
What is a weighted average?
A weighted average is a mean where each value is multiplied by a weight that reflects its importance. The formula is: Weighted Average = Σ(value × weight) / Σ(weights).
How do you calculate weighted average?
To calculate weighted average: 1) Multiply each value by its weight, 2) Sum all the weighted values, 3) Sum all the weights, 4) Divide the sum of weighted values by the sum of weights.
When do you use weighted average instead of regular average?
Use weighted average when different values have different levels of importance or frequency. Common examples include GPA calculations, portfolio returns, and survey data with varying sample sizes.