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In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the outcome or response variable, or a label in machine learning parlance) and one or more error-free independent variables (often called regressors, predictors, covariates, explanatory ...
Dec 1, 2017 · Although Pearson did develop a rigorous treatment of the mathematics of the Pearson Product Moment Correlation (PPMC), it was the imagination of Sir Francis Galton that originally conceived modern notions of correlation and regression.
- Jeffrey M. Stanton
- 2001
So it was with regression analysis. The history of this particular statistical technique can be traced back to late nineteenth-century England and the pursuits of a gentleman scientist, Francis Galton.
Nov 6, 2015 · Regression analysis as we know it today is primarily the work of R.A. Fisher, one the most renowned statisticians of the 20th Century. Fisher combined the work of Gauss and Pearson to develop a fully realized theory of the properties of least squares estimation.
Aug 25, 2011 · Many words in our statistical lexicon were coined by Galton. For example, correlation and deviate are due to him, as is regression, and he was the originator of terms and concepts such as quartile, decile and percentile, and of the use of median as the midpoint of a distribution 2.
Simple regression and correlation form the basis of what is generally referred to today as regression analysis. In general, regres- sion analysis is a statistical technique that attempts to predict the values of one variable using the values of one or more other variables. By
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It is argued that correlation and regression analysis emerged from a particular social and cultural context, and that this context entered into the very nature of those techniques. The paper is divided into three sections.
