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Lecture 16 2010

# Lecture 16 2010 - IV MultipleRegression A Introduction B...

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1 IV. Multiple Regression . A. Introduction B. CRM C. Estimation D. Interpretation of Parameter Estimates E. Properties of Estimators IV. Multiple Regression A. Introduction . 1. Multiple regression – measure the effects of several independent variables on the dependent variable. 2 Write a multiple regression population 2. Write a multiple regression population regression equation: Y i = β 0 + β 1 X 1i + β 2 X 2i +…+ β k X ki + u i . B. Classical Regression Model – again the assumptions, and we add one. 1. Y i = β 0 + β 1 X 1i + β 2 X 2i + … β k X ki + u i . 2. The Xs are not random variables. 3. E[ u | X i ] = 0. 4. Var(u | X i ] = σ 2 . 5. Cov( u i , u j ) = E[u i u j ] = 0. 6. u ~ Normally. 7. No perfect linear associations among Xs.

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