MAPE Calculator
What is Mean Absolute Percentage Error Calculator?
MAPE measures the average percentage error between predicted and actual values.
๐ Key Inputs:
- Observed Values = actual data
- Predicted Values = forecasted data
๐ Core Output:
- MAPE (%) = average error percentage
๐ It answers: How accurate are my predictions in percentage terms?
This metric is widely used in:
- Forecasting models
- Business analytics
- Demand planning
- Financial projections
For deeper error analysis, you can combine this with a percentage error calculator.
How to Use Mean Absolute Percentage Error Calculator?
Using the calculator is simple:
Step 1: Enter observed values (comma separated)
Step 2: Enter predicted values (same length)
Step 3: Click calculate
Step 4: View results instantly
๐ Youโll get:
- MAPE percentage
- Number of data points used
Example:
Observed = 100, 200, 300
Predicted = 110, 190, 310
Result = average percentage error across all points
For trend tracking, combine results with a cumulative percentage calculator.
How to Calculate Mean Absolute Percentage Error Manually?
Manual calculation helps you understand model accuracy and validate results step by step.
Mean Absolute Percentage Error Formula
MAPE (%) = (1 / n) ร ฮฃ |(Observed โ Predicted) รท Observed| ร 100
Step-by-Step Breakdown
Example:
Observed = 100, 200
Predicted = 110, 180
Step 1: Calculate individual errors
| Observed | Predicted | Error |
|---|---|---|
| 100 | 110 | 10% |
| 200 | 180 | 10% |
Step 2: Average errors
(10% + 10%) รท 2 = 10%
๐ MAPE = 10%
5 Example Problems of Mean Absolute Percentage Error
These examples show how forecast accuracy varies across different datasets.
Example 1: High accuracy
Observed = 100, 200
Predicted = 102, 198
Result โ 2%
Example 2: Moderate accuracy
Observed = 100, 200
Predicted = 110, 190
Result โ 10%
Example 3: Low accuracy
Observed = 100, 200
Predicted = 130, 150
Result โ 25%
Example 4: Perfect prediction
Observed = 50, 60
Predicted = 50, 60
Result = 0%
Example 5: Mixed dataset
Observed = 100, 150, 200
Predicted = 90, 160, 210
Result โ 8โ10%
How to Interpret Your MAPE Results?
MAPE reflects forecast accuracy.
| MAPE % | Meaning |
|---|---|
| 0โ5% | Very accurate |
| 5โ10% | Good |
| 10โ20% | Acceptable |
| Above 20% | Poor accuracy |
๐ Example: If MAPE increases from 8% to 15%, you can find percentage increase in error to understand performance decline.
When Should You Use Mean Absolute Percentage Error Calculator?
Use this tool when:
- Evaluating forecasting models
- Comparing prediction accuracy
- Monitoring business performance
- Analyzing demand forecasts
- Improving data models
What Are The Limitations of MAPE?
- Cannot handle zero observed values
- Sensitive to small denominators
- Ignores direction of error
- May mislead with extreme values
Related Calculators
To expand your data analysis:
- Measure variability with percentage standard deviation calculator
- Track trends using month over month percentage calculator
- Convert percent to decimal using percentage to decimal tool
- Analyze ratios using ratio to percentage calculator
- Convert fractions using fraction to percentage calculator
- Measure averages with average percentage calculator
- Analyze knitting decrease using Knitting Decrease Calculator
- Understand percentage drop calculations with percentage drop calculator
FAQs About Mean Absolute Percentage Error Calculator
Q1: What is MAPE?
A1: It is the average percentage difference between predicted and actual values.
Q2: What is a good MAPE value?
A2: Typically below 10% is considered good.
Q3: Why use percentage error instead of absolute error?
A3: It allows comparison across different scales.
Q4: Can MAPE be zero?
A4: Yes, when predictions are perfectly accurate.
Q5: What happens if observed value is zero?
A5: MAPE cannot be calculated because of division by zero.
