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Both calculators run independently — change the inputs on either side to compare results.

Linear Regression Calculator

Fit a least-squares regression line y = a + b·x to paired x and y values and read off the slope, intercept, or coefficient of determination (r²). Used in forecasting, trend analysis, and any setting where you want to quantify how much y changes with x.

X Values (comma separated)

Y Values (comma separated)

Output

Fill in the required fields to see your result.

Statistics

Correlation Coefficient Calculator

Compute the Pearson correlation coefficient (r) between two variables from paired summary statistics — n, Σxy, Σx, Σy — to measure how strongly they move together linearly. The number ranges from −1 (perfect negative linear relationship) through 0 (no linear relationship) to +1 (perfect positive linear relationship).

Number of Pairs

Sum of XY

Sum of X

Sum of Y

Sum of X²

Sum of Y²

Fill in the required fields to see your result.

Key differences

	Linear Regression Calculator	Correlation Coefficient Calculator
Category	Statistics	Statistics
Inputs required	3	6
Result	Result	Correlation Coefficient
What it does	Fit a least-squares regression line y = a + b·x to paired x and y values and read off the slope, intercept, or coefficient of determination (r²). Used in forecasting, trend analysis, and any setting where you want to quantify how much y changes with x.	Compute the Pearson correlation coefficient (r) between two variables from paired summary statistics — n, Σxy, Σx, Σy — to measure how strongly they move together linearly. The number ranges from −1 (perfect negative linear relationship) through 0 (no linear relationship) to +1 (perfect positive linear relationship).