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Simple Linear Regression Calculator

Calculate slope, intercept, R squared, residual error, and slope significance.

Input

Configure inputs first. Final results, visuals, downloads, and copy summary remain hidden until Calculate Regression succeeds.

Input mode

Manual inputLocal CSV input

Paired x, y valuesOne pair per line, such as 1, 2.

AlphaConfidence levelAlternative

What This Tool Does

The Simple Linear Regression Calculator fits one predictor and one response after Calculate Regression is clicked. It warns about extrapolation and causal overinterpretation.

Method

Ordinary least squares estimates the intercept and slope by minimizing squared residuals.

Worked Example

Pairs 1,2; 2,4; 3,5; 4,8 produce a positive slope and fitted line after calculation.

Common Mistakes

Extrapolating beyond observed x values.
Treating regression as causal proof.

Limitations

Multiple regression and logistic regression are out of scope.
Outliers can strongly affect least squares.

References

NIST e-Handbook: Linear Least Squares Regression: NIST/SEMATECH e-Handbook of Statistical Methods, linear least squares regression.

What is R squared?

It is the share of response variability explained by the fitted linear model in this sample.

What is residual standard error?

It estimates typical residual size around the fitted line.

Is extrapolation safe?

No. Predictions outside the observed x range can be unreliable.

What does the slope p-value test?

It tests whether the population slope differs from zero under model assumptions.

Does the Simple Linear Regression Calculator calculate automatically while I type?

No. Inputs and CSV previews never produce final statistics until the explicit calculate button is clicked.

Are CSV files uploaded?

No. Selected CSV files are processed locally in the browser. ScholarTool does not upload the file to a third-party calculation or data-analysis API.

Can a p-value prove a hypothesis?

No. A p-value is evaluated against the selected alpha level under stated assumptions; it does not prove the null or alternative hypothesis.

Engineering disclaimer

This statistics tool is intended for education, planning, and preliminary analysis. Review assumptions, study design, and professional statistical judgement before using results in research, engineering, safety, regulatory, or compliance decisions. ScholarTool does not prove hypotheses or replace qualified analysis.

Need Professional Support?

ScholarTool is powered by ScholarEase Consultancy Services LLP. Professional engineering, simulation, research, and technical documentation support is available through the connected services website.

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Last reviewed: 2026-07-07

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Engineering disclaimer

Simple Linear Regression Calculator

Input

What This Tool Does

Method

Worked Example

Common Mistakes

Limitations

References

Related Tools

Engineering disclaimer

Need Professional Support?

Simple Linear Regression Calculator

Input

What This Tool Does

Method

Worked Example

Common Mistakes

Limitations

References

Related Tools

Engineering disclaimer

Need Professional Support?