विधियों की तुलना करें

	पियर्सन प्रोडक्ट-मोमेंट सहसंबंध	सरल रैखिक प्रतिगमन
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Hypothesis test	Regression model
उद्भव वर्ष	1895	1805
प्रवर्तक	Karl Pearson	Adrien-Marie Legendre (least squares, 1805); Francis Galton (regression concept, 1886)
प्रकार	Parametric correlation	Parametric bivariate regression
मौलिक स्रोत	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]
उपनाम	pearson r, product-moment correlation, bivariate correlation, Pearson Korelasyon Analizi	SLR, ordinary least squares regression, OLS regression, bivariate regression
संबंधित	4	7
सारांश	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.