This tool fits regression models to your data and provides detailed statistics including coefficient estimates, standard errors, p-values, R², ANOVA, and residual diagnostics. A scatter plot with the fitted curve is generated for visual inspection.
How to Use
- Enter X and Y values in the text areas — comma, space, or newline separated. Both columns must have the same number of values (at least 3).
- Select a model from the dropdown.
- Click Calculate to generate the results and plot.
- Use the Predict box to estimate y for a new x value.
Models
| Model | Equation | Use case |
|---|---|---|
| Linear | y = a + bx | Simple linear relationship |
| Quadratic | y = a + bx + cx² | Curvature with one bend (≥ 4 points) |
| Cubic | y = a + bx + cx² + dx³ | Two bends (≥ 5 points) |
| Exponential | y = a·e^(bx) | Growth/decay (y > 0) |
| Power | y = a·x^b | Allometric scaling (x > 0, y > 0) |
| Logarithmic | y = a + b·ln(x) | Saturating relationship (x > 0) |
Output
- Equation with fitted coefficients
- Coefficient table with estimate, standard error, t-statistic, and p-value
- Goodness of fit: R², adjusted R², F-statistic with p-value
- ANOVA table: decomposition of variance into regression and residual components
- Residuals table (collapsible) with fitted values and residuals; points with |standardized residual| > 2 are flagged
- Scatter plot with fitted curve and R² annotation
