Curve Fitting Workbench
Compare linear, quadratic, cubic, exponential, power and logarithmic fits with residual plots, error metrics, equations and editable data.
Explore a preset, then edit the controls. Results update when you leave a field or select an option.
A worked example
A quadratic fit to (-2,4), (-1,1), (0,0), (1,1), (2,4), (3,9) recovers y = x² to floating-point precision.
Scope and practical limits
3–500 numeric data pairs, no CSV header. Polynomial degree at most 3. Power/logarithmic models require positive X; exponential/power require positive Y. No weighted fit or confidence interval.
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Using Curve Fitting Workbench
Compare linear, quadratic, cubic, exponential, power and logarithmic fits with residual plots, error metrics, equations and editable data.
- Choose a preset to see a worked example, then edit the labeled values.
- Inspect the live chart and result summary. Read any warnings about assumptions or unsupported inputs.
- Review the calculation table, which shows 50 rows per page. Exports contain all available result rows.
- Export the chart as SVG or PNG and the data as CSV or JSON. Save a project to reopen your inputs later.
Example
A quadratic fit to (-2,4), (-1,1), (0,0), (1,1), (2,4), (3,9) recovers y = x² to floating-point precision.
Questions & answers
Why is the equation expressed using z?
X values are centered and scaled for numerical stability. The exported equation defines z explicitly so it can be reused correctly.
Does the highest R² prove the best model?
No. Additional parameters can overfit. Check residuals and the data-generating process; do not treat extrapolated values as reliable forecasts.
Can I keep editing later?
Save project downloads the inputs and options as JSON. Open project restores that file. Undo and redo remain available during this tab session.
Are images and data exports free?
Yes. Chart SVG/PNG and data CSV/JSON exports do not require an account. Specialized exports are shown beside the result when supported.
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