Regression analysis has been one of the most widely used statistical methodologies for analyzing relationships among variables during the past fifty years. Due to its flexibility, usefulness, applicability, theoretical and technical succinctness, it has become a basic statistical tool for solving problems in the real world. In order to apply regression analysis effectively, it is necessary to understand both the underlying theory and its practical application. This book explores conventional topics as well as recent practical developments, linking theory with application. Intended to continue from where most basic statistics texts end, it is designed primarily for advanced undergraduates, graduate students and researchers in various fields of engineering, chemical and physical sciences, mathematical sciences and statistics.
Chapter 1and Statistics Chapter 3: Simple Linear Regression Chapter 4: Random Vectors and Matrix Algebra Chapter 5: Multiple Regression Chapter 6: Residuals, Diagnostics and Transformations Chapter 7: Further Applications of Regression Techniques Chapter 8: Selection of Regression Model Chapter 9: Multicollinearity: Diagnosis and Remedies