LOCAL DATA ANALYSIS
Linear regression calculator
Fit a least-squares line to paired values. Calculate slope, intercept and R², view the scatter plot and fitted line, and export your result.
Least-squares fitted line
5 paired observations. This describes the input data; it does not validate predictions or a causal effect.
- Slope
- 0.62
- Intercept
- 15.4
- R²
- 0.9907216
Formula and method
ŷ = intercept + slope × X; slope = Σ[(x − mean X)(y − mean Y)] ÷ Σ(x − mean X)²
Simple linear regression fits one numeric outcome to one numeric predictor. Least squares selects the line that minimizes the sum of squared vertical residuals.
Worked example
For X = 10, 20, 30, 40, 50 and Y = 21, 29, 33, 41, 46, the fitted line is ŷ = 15.4 + 0.62 × X. R² is approximately 0.9907.
What the result can tell you
X must vary and at least two complete pairs are needed. R² describes in-sample fit and is not predictive accuracy. Constant Y gives a zero slope but makes R² undefined in this calculator. Inspect outliers and residual patterns; extrapolation beyond the input range is not validated here.
Method reference: NIST: linear least squares.