Regression Calculator
Online regression calculator. Paste or type your X–Y data, get slope, intercept, correlation (r), R², standard error, ANOVA table and predicted values. Includes scatter plot and residuals.
Full original guide (expanded)
Regression Calculator
Enter X–Y pairs and this tool will run a simple linear regression of Y on X. You get the regression line (slope & intercept), the correlation coefficient, R², standard error, and a quick ANOVA table. You can also enter an X value to get a predicted Y.
| # | X | Y | |
|---|---|---|---|
| 1 | |||
| 2 | |||
| 3 |
Equation
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r (correlation)
—
R²
—
Predicted Y
—
Blue dots: data points; Orange line: fitted regression line (first 60 points shown).
ANOVA (simple regression)
| Source | SS | df | MS |
|---|---|---|---|
| Regression | — | — | — |
| Residual (Error) | — | — | — |
| Total | — | — | — |
Formulas used
Regression line: \( y = a + bx \)
\( b = \dfrac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2} \)
\( a = \bar{y} - b\bar{x} \)
Correlation: \( r = \dfrac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2 \sum (y_i - \bar{y})^2}} \)
R²: \( R^2 = 1 - \dfrac{\text{SSE}}{\text{SST}} \)
Interpreting results
- r close to ±1 ⇒ strong linear relationship.
- R² close to 1 ⇒ model explains most of the variability.
- Check the scatterplot to ensure linearity – regression is a linear model.
Formula (LaTeX) + variables + units
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Regression line: \( y = a + bx \) \( b = \dfrac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2} \) \( a = \bar{y} - b\bar{x} \) Correlation: \( r = \dfrac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2 \sum (y_i - \bar{y})^2}} \) R²: \( R^2 = 1 - \dfrac{\text{SSE}}{\text{SST}} \)
- No variables provided in audit spec.
- NIST — Weights and measures — nist.gov · Accessed 2026-01-19
https://www.nist.gov/pml/weights-and-measures - FTC — Consumer advice — consumer.ftc.gov · Accessed 2026-01-19
https://consumer.ftc.gov/
Last code update: 2026-01-19
- Initial audit spec draft generated from HTML extraction (review required).
- Verify formulas match the calculator engine and convert any text-only formulas to LaTeX.
- Confirm sources are authoritative and relevant to the calculator methodology.