Linear Regression
Linear regression finds the best-fit line y = mx + b through a set of data points by minimizing the sum of squared residuals.
Slope: m = (nΣxy - ΣxΣy) / (nΣx² - (Σx)²)
Intercept: b = ȳ - m×x̄
Linear Regression Calculator
Enter X and Y data sets to find the best-fit line and make predictions.
Regression Equation
y = 0x + 0
Slope (m)
0
Intercept (b)
0
r²
0
Correlation (r)
0
Predicted y
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Summary
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