Comparar métodos

	Coeficiente de correlación de momento producto de Pearson	Regresión Lineal Simple
Campo	Estadística	Estadística
Familia	Hypothesis test	Regression model
Año de origen	1895	1805
Autor original	Karl Pearson	Adrien-Marie Legendre (least squares, 1805); Francis Galton (regression concept, 1886)
Tipo	Parametric correlation	Parametric bivariate regression
Fuente seminal	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates.	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]
Alias	pearson r, product-moment correlation, bivariate correlation, Pearson Korelasyon Analizi	SLR, ordinary least squares regression, OLS regression, bivariate regression
Relacionados	4	7
Resumen	The Pearson product-moment correlation coefficient (r) is a parametric measure of the direction and strength of the linear association between two continuous variables. Introduced by Karl Pearson in 1895, it remains the most widely used bivariate correlation statistic in the social, health, and natural sciences. The coefficient ranges from −1 (perfect negative linear relationship) to +1 (perfect positive), with 0 indicating no linear association.	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.