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This lecture focuses on the topic of restrictions in multiple regression analysis. It covers the F-test for assessing restrictions imposed on regression estimates and explores the estimation of model variance. Participants will learn to apply the Shazam program for testing restrictions, with practical examples drawn from the HGJ framework. By the end of the lecture, learners will gain insights into testing hypotheses and understanding parameter estimates within the context of multiple regression models.
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