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Simple Linear Regression

Simple linear regression is the foundational parametric method for modelling a straight-line relationship between one continuous predictor and one continuous outcome, estimating the slope and intercept by ordinary least squares (OLS). The least squares principle was first published by Adrien-Marie Legendre in 1805, and Francis Galton introduced the concept of regression to the mean in 1886, coining the term that names the entire family of methods.

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Simple Linear Regression (OLS)

Taxonomisk metodpost · regression-model / statistics

Legendre, A. M. (1805). Nouvelles méthodes pour la détermination des orbites des comètes. Firmin Didot, Paris. [Appendix: Sur la méthode des moindres quarrés, pp. 72–80] · URL
Galton, F. (1886). Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263. · DOI 10.2307/2841583
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to Linear Regression Analysis (6th ed.). Wiley. · ISBN 978-1119578727

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Used in the same domainIndependent t-testmachine-suggested · Relational suggestion, not evidence.See alsoLogistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyMultiple Linear Regressionmachine-suggested · Relational suggestion, not evidence.Used in the same domainOne-way ANOVAmachine-suggested · Relational suggestion, not evidence.Used in the same domainPearson Correlationmachine-suggested · Relational suggestion, not evidence.Same method familyPolynomial Regressionmachine-suggested · Relational suggestion, not evidence.See alsoRidge Regressionmachine-suggested · Relational suggestion, not evidence.