3Multiple CLRM & DV(LC)(1).docx

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Tutor Session – Multiple Linear Regression Model & Dummy Variable Multiple Regression o k-variable Regression model o OLS & 10 Assumptions Estimated parameters/Variance/Sample Variance Interpretation o Finite Properties – BLUE o Goodness of Fit R-square Vs. Adjusted R-square Partial Correlation o **STATA Output o Hypothesis Testing Individual Test Overall Test ANOVA Table (F-test) Adding Variable (F-test) Linear Restriction Test Equality of 2 parameters (t-test) Linearity of 2 parameters (t-test) Equality of more-than-2 parameters (F-test) Linearity of parameters (F-test) Chow test of Structural Change o **STATA Output Dummy Variable o What is Dummy Variable? o Cautions on using Dummy o 4 Basic Models for Dummy Variables

Transcript of 3Multiple CLRM & DV(LC)(1).docx

Tutor Session Multiple Linear Regression Model & Dummy Variable Multiple Regression k-variable Regression model OLS & 10 Assumptions Estimated parameters/Variance/Sample Variance Interpretation Finite Properties BLUE Goodness of Fit R-square Vs. Adjusted R-square Partial Correlation **STATA Output Hypothesis Testing Individual Test Overall Test ANOVA Table (F-test) Adding Variable (F-test) Linear Restriction Test Equality of 2 parameters (t-test) Linearity of 2 parameters (t-test) Equality of more-than-2 parameters (F-test) Linearity of parameters (F-test) Chow test of Structural Change **STATA Output Dummy Variable What is Dummy Variable? Cautions on using Dummy 4 Basic Models for Dummy Variables ANOVA Model (Only Intercept) ANCOVA Model (Intercept & Slope) Dummy & Quantitative interaction Dummy Variables interaction Implication Chow Test/Seasonal/Piecewise Semilog model & Dummy Variable **STATA Output