Practical Regression: Regression Basics Harvard Case Solution & Analysis

This is the second in a series of lectures, which, if linked together in the book, could be entitled "Practical Regression." Goal score in addition to the theoretical content of most statistics texts with practical advice based on nearly three decades of experience of the author, along with more than a hundred years experience of colleagues who offered advice. As the title "Practical Regression" suggests, these notes guide performing the regression in practice. This technical note summarizes the key features of the regression analysis. Students who read this note will be able to explain the fundamental principles of regression, including (1) the regression equation as alegbraic (2) dummy variables and nonlinear conditions, and (3) R-square and goodness of fit, and (4) the importance of accountability and the economic significance of the regression coefficients. After completion of this article, students will be prepared for the study of special topics in regression, which are discussed in other notes in this series. "Hide
by David Dranove Source: Kellogg School Management 15 pages. Publication Date: June 11, 2012. Prod. #: KEL636-PDF-ENG

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