PPT-Chapter 9: Regression

Alexander Swan amp Rafey Alvi Residuals Grouping No regression analysis is complete without a display of the residuals to check that the linear model is reasonable Residuals often reveal subtleties that were not clear from a plot of the original data. Di64256erentiating 8706S 8706f Setting the partial derivatives to 0 produces estimating equations for the regression coe64259cients Because these equations are in general nonlinear they require solution by numerical optimization As in a linear model isavectorofparameterstobeestimatedand x isavectorofpredictors forthe thof observationstheerrors areassumedtobenormallyandindependentlydistributedwith mean 0 and constant variance The function relating the average value of the response to the pred C. orrelation and Regression. 10-1 Review and Preview. 10-2 Correlation. 1. 0-3 Regression. 1. 0-4 Variation and Prediction Intervals. 10-5 Multiple Regression. 10-6 Modeling. MAT 155 Statistical Analysis. Intro:. This section is going to focus on relationships among several variables for the same group of individuals. In these relationships, does one variable cause the other variable to change?. Explanatory Variable. Regression Wisdom. Teaching Tip. While you add a little “wisdom” to your students’ understanding of regression, you have a great opportunity to review the concepts in chapter 7.. This can also naturally lead to reassessment opportunities.. McGraw-Hill/Irwin. Copyright © 2011 by the McGraw-Hill Companies, Inc. All rights reserved.. Basic Estimation. Parameters. The coefficients in an equation that determine the exact mathematical relation among the variables . Fun facts about the regression line. Equation of regression line: . If we convert our X and Y scores to . z. x. and . z. y. , the regression line through the z-scores is:. Because the means of the z-scores are zero and the standard deviations are 1.. Due 10/30/15. 42 Points. A regression line is a ________ line that describes how a __________ variable y changes as an ____________ variable x changes. You can use a regression line to predict the value of y for any value of x by substituting this x into the equation of the line.. Regression Wisdom. 1. Percentage of Men Smokers (18 – 24 years of age) from 1965 through 2009. The centre for Disease Control and Prevention track cigarette smoking in the US. How has the percentage of people who smoke changed since the danger became clear during the last half of the 20. Section 3.2. Least-Squares Regression. Least-Squares Regression. MAKE predictions using regression lines, keeping in mind the dangers of extrapolation.. CALCULATE and interpret a residual.. INTERPRET the slope and . : A British biometrician, Sir Francis Galton, defined regression as ‘stepping back towards the average’. He found that the offspring of abnormally tall or short parents tends to regress or step back to average.. Fun facts about the regression line. Equation of regression line: . If we convert our X and Y scores to . z. x. and . z. y. , the regression line through the z-scores is:. Because the means of the z-scores are zero and the standard deviations are 1.. . Lecture compiled by. Dr. . Parminder. . Kaur. Assistant Professor. Department of Commerce. For . B.Com. (. Prog. ) II . Sem. . Sec A. SIMPLE . LINEAR . REGRESSION. DEFINITION OF . REGRESSION . Regression Trees. Characteristics of classification models. model. linear. parametric. global. stable. decision tree. no. no. no. no. logistic regression. yes. yes. yes. yes. discriminant. analysis.