Linear Regression Calculator

Linear regression finds the straight line that best describes the relationship between an input x and an output y. This calculator uses ordinary least squares, which picks the slope and intercept that make the total squared distance between the line and your data points as small as possible.

R-squared, the coefficient of determination, is the share of the variation in y that the line explains, on a scale from 0 to 1. A value of 1 means every point sits exactly on the line, while a value near 0 means the line explains almost none of the variation. For example, r-squared of 0.81 means the line accounts for 81 percent of the variance in y.

The slope equals the covariance of x and y divided by the variance of x (Sxy divided by Sxx). The intercept is the mean of y minus the slope times the mean of x, which forces the line to pass through the average point. Together they give the equation y = slope times x plus intercept.

The correlation coefficient r ranges from -1 to 1 and shows both the strength and direction of the relationship: positive means y rises with x, negative means it falls. R-squared is simply r multiplied by itself, so it is always between 0 and 1 and drops the sign, measuring only how much of the variation is explained.

A line is defined by two points, so a single point cannot fix a slope. The x values also cannot all be identical, because that would be a vertical line with no finite slope and the formula would divide by zero. The calculator asks for two or more points that vary in x.

No. The regression runs entirely in your browser, so your data points never leave your device and nothing is stored on a server.