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Unformatted text preview: Chapter 15 Multiple Regression Outline: • Multiple Regression Model • Least Squares Method • Multiple Coefficient of Determination • Model Assumptions • Testing for Significance • Using the Estimated Regression Equation for Estimation and Prediction • Qualitative Independent Variables • Residual Analysis The Multiple Regression Model: y = + 1 x 1 + 2 x 2 + . . . + p x p + The Multiple Regression Equation: E( y ) = + 1 x 1 + 2 x 2 + . . . + p x p The Estimated Multiple Regression Equation: = b + b 1 x 1 + b 2 x 2 + . . . + b p x p The Least Squares Method : Least Squares Criterion: The formulas for the regression coefficients bo,b 1 b2, ••• bp involve the use of matrix algebra. We will rely on computer software packages to perform the calculations. • Interpretation of Coefficients bi represents an estimate of the change in y corresponding to a one-unit change in Xi when all other independent variables are held constant. The Multiple Coefficient of Determination: • Relationship Among SST, SSR, SSE SST = SSR + SSE • Multiple Coefficient of Determination R 2 = SSR/SST • Adjusted Multiple Coefficient of Determination where n is the number of observations and...
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This note was uploaded on 12/06/2011 for the course MGMT 305 taught by Professor Priya during the Fall '08 term at Purdue University.
- Fall '08