Linear Regression Calculator
Fit a straight line through up to 4 paired X and Y values and predict Y for any given X using ordinary least squares.
Only the first this-many X/Y pairs below are used (2 to 4 pairs).
Your results
Calculation breakdown
- Slope
- m = Σ(x − x̄)(y − ȳ) / Σ(x − x̄)²
- Intercept
- b = ȳ − m × x̄
- Prediction
- ŷ = m×x + b
Worked example
Fitting a line through (1,2), (2,4), (3,5) and (4,8) gives roughly y = 2x − 0.5, predicting y ≈ 9.5 for x = 5.
Assumptions
- Fits a simple ordinary least-squares straight line; it does not capture curved or non-linear relationships.
- With only 2–4 points, the fitted line is illustrative and can be sensitive to a single unusual value.
How this calculator works
Enter up to 4 paired X and Y values and a value of X to predict. The calculator fits an ordinary least-squares straight line through the data and returns the slope, intercept and predicted Y value.
Frequently asked questions
What do the slope and intercept mean?
The slope shows how much Y changes for each one-unit increase in X, and the intercept is the predicted Y value when X is zero.
Can I trust predictions far outside my data range?
No, extrapolating well beyond your original X values is unreliable, since the true relationship may not stay linear outside that range.
What if my data isn't linear?
A straight-line fit will poorly describe curved relationships; check a scatter plot first to see if a linear model is appropriate.