Linear Regression Calculator
Fit an ordinary least-squares line to paired samples and report slope, intercept, and R squared.
Description
Fit an ordinary least-squares line to paired samples and report slope, intercept, and R squared.
Linear Regression Calculator is a focused tool for the following task. Fit an ordinary least-squares line to paired samples and report slope, intercept, and R squared. It reports Intercept, R squared, Slope from the values you provide rather than inventing measurements, coefficients, or professional judgment that are not part of the input.
When to use Linear Regression
Use this calculation to reproduce a defined quantitative method when the observations, units, sampling process, and assumptions match the method shown here.
- X values
- Required list. Predictor observations.
- Y values
- Required list. Response observations aligned with the predictor values.
The cited overview of Regression analysis supplies background for the terminology and domain context used by this tool.1
How Linear Regression works
Fit an ordinary least-squares line to paired samples and report slope, intercept, and R squared. Inputs are interpreted exactly in the displayed units and the calculation returns the following fields without presentation rounding.
- Intercept
- Returned number. Fitted value of y when x is zero.
- R squared
- Returned number. Fraction of response variance explained by the fitted line.
- Slope
- Returned number. Fitted change in y per unit change in x.
Limitations and assumptions
- A numerical result does not by itself establish data quality, causation, representativeness, independence, distributional fit, or practical significance.
- Use finite inputs in the displayed units, preserve source measurements and assumptions, and independently verify consequential decisions.
Alternative or Complementary approaches
Inspect the underlying data, visualize its distribution, report uncertainty and sample size, and compare the result with a robust or domain-specific method where appropriate.
References
-
Regression analysis — Wikipedia contributors
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