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Regression Analysis: Characterization of Points on the Line of Regression and Prediction -, Study notes of Data Analysis & Statistical Methods

This lecture outline covers the characterization of points on the line of regression, finding the intercept and slope, predicting y values for given x values, and the optimality of the regression predictor for approximately elliptical plots. It also explains the relationship between r-squared and the fraction of variance explained by the sample regression.

Typology: Study notes

Pre 2010

Uploaded on 07/28/2009

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koofers-user-p8v 🇺🇸

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Download Regression Analysis: Characterization of Points on the Line of Regression and Prediction - and more Study notes Data Analysis & Statistical Methods in PDF only on Docsity! Lecture outline 2 - 13 - 09 Part of the period will cover numerical examples as in 2-11-09. The rest will be devoted to the points below. 1. Important characterization of all points Hx, yL which lie on the line of regression : y - y x - x = r sy sx Slope = r sy sx = r s̀y s̀x = r y2 - y2 x2 - x2 pg. 197 2. Taking x = 0 in y - y 0 - x = r sy sx gives intercept = y - x slope pg. 198 3. For every x, solving for y in y - y x - x = r sy sx gives predicted y = pt on regr line : pred y = y + Hx - xL slope 2 Lecture Outline 2-13-09.nb
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