Regression Analysis By Example Using R
A STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSIS
In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.
The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R.
Readers will also find:
Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.
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Ali S. Hadi, PhD, Fellow ASA (1997), Member ISI (1998), Fellow AAS (2019) is Distinguished University Professor and former Chair of the Department of Mathematics and Actuarial Science at the American University in Cairo (AUC). He is also the Founder of the Actuarial Science Program at AUC (2004), the Founder of the Data Science Program at AUC (2019), and the former Vice Provost and Director of Graduate Studies and Research at AUC. Dr. Hadi is also a Stephen H. Weiss Presidential Fellow and Professor Emeritus at Cornell University, USA. He is the author and co-author of four other books and numerous articles. For more info, see his Website at: www1.aucegypt.edu/faculty/hadi.
A STRAIGHTFORWARD AND CONCISE DISCUSSION OF THE ESSENTIALS OF REGRESSION ANALYSIS
In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.
The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R.
Readers will also find:
Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.
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