Linear Regression Calculator

This linear regression calculator fits a simple least-squares line to paired x and y values. It reports the slope, intercept, Pearson correlation r, r², residual standard error, and a two-sided p-value for the slope, and it draws a scatter plot with the fitted line.

Linear regression calculator

Paste paired x and y values to get the slope, intercept, r, and r², with a scatter plot and the fitted line.

Use a period for decimals. Separate values with commas, spaces, or new lines. X and Y must have the same length (at least three pairs).

Calculator loading… If the form does not return a result, wait a moment and try again.

Simple linear regression formulas

b₁ = Sxy / Sxx, where Sxy = Σ(x − x̄)(y − ȳ) and Sxx = Σ(x − x̄)².

b₀ = ȳ − b₁ x̄, so the fitted line is ŷ = b₀ + b₁ x.

r = Sxy / √(Sxx Syy), and r² is the fraction of the variation in y explained by the line.

The residual standard error is s = √(SSE / (n−2)), and the standard error of the slope is s / √Sxx. Then t = b₁ / SE(b₁) with df = n − 2.

Worked example

For the points (1, 2.1), (2, 3.9), (3, 6.2), (4, 7.8), (5, 10.1), (6, 11.7), (7, 14.2), (8, 15.8), the fitted line is approximately ŷ = 0.082 + 1.985 x. Pearson r is about 0.999, so r² is about 0.997, and the slope is clearly different from zero.

Related calculators and guides

Frequently asked questions

What is r² in linear regression?

r² is the proportion of the variation in y that is accounted for by the linear relationship with x. A value of 1 means the points fall exactly on the line; a value near 0 means the line explains little of the variation.

Is this multiple regression?

No. This tool fits one explanatory variable. Multiple regression with two or more predictors is a different model.

What assumptions does the slope p-value use?

The t-test for the slope assumes that the residuals are approximately normal with constant variance, that the pairs are independent, and that the relationship is linear. The fitted line itself is still the least-squares line even if those assumptions fail, but the p-value may not be reliable.

How is this different from correlation?

Correlation measures the strength of a linear association and does not single out a response variable. Regression also gives an equation for predicting y from x. The Pearson r from this calculator is the same r you would get from the correlation coefficient calculator.

How should I format the data?

Paste x in one box and y in the other, in the same order, with at least three pairs. Use periods for decimals and separate values with commas, spaces, or new lines.