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Mean Squared Error and RMSE Calculator — result sheet
Calculate mean squared error and root mean squared error from equal-length actual and predicted lists.
Inputs used
Results
Visual chart
Breakdown
Calculation steps
Returned data table
Formula and methodology
Formula: MSE=Σ(actual−predicted)²/n; RMSE=√MSE.
Squared error is averaged before the square root so the scale of the original target remains visible.
This result follows the calculator's declared inputs, precision, validation boundaries, and model limits.
Input contract
- Actual values — Enter 2 to 200 finite values separated by commas or spaces.
- Predicted values — Enter the same number of finite values.
Worked example
| Input | Value |
|---|---|
| Actual values | 3, 5, 7, 9 |
| Predicted values | 2, 6, 8, 8 |
MSE =1; RMSE =1.
Assumptions and limits
- Actual and predicted lists contain the same number of finite values.
- Each pair is aligned by position and all cases have equal weight.
- Cross-validation, calibration, asymmetric costs, and data leakage are not modeled.
Calculator note
Source and methodology
Use the official WorldCalculate methodology policy for the source, formula, precision, and boundary standards behind this calculator.
Planning estimate, not financial, medical, legal, or professional advice. © WorldCalculate — reuse with attribution. Built and curated by Hassan ALRowaie.
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