## Modern Regression Methods"Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one." ( The American Statistician) "The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite. I also highly recommend it to practitioners who want to solve real-life prediction problems." ( The book provides a unique treatment of fundamental regression methods, such as diagnostics, transformations, robust regression, and ridge regression. Unifying key concepts and procedures, this new edition emphasizes applications to provide a more hands-on and comprehensive understanding of regression diagnostics. New features of the -
A revised chapter on logistic regression, including improved methods of parameter estimation -
A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression -
A wealth of new and updated exercises with worked solutions -
An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures -
Updated references at the end of each chapter that direct the reader to the appropriate resources for further study
An accessible guide to state-of-the-art regression techniques, |

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### Contents

Introduction | 1 |

Diagnostics and Remedial Measures | 17 |

Regression with Matrix Algebra | 29 |

Introduction to Multiple Linear Regression | 34 |

Plots in Multiple Regression | 49 |

Transformations in Multiple Regression | 58 |

Selection of Regressors | 70 |

Polynomial and Trigonometric Terms | 80 |

Nonparametric Regression | 95 |

Robust Regression | 101 |

Ridge Regression | 107 |

Nonlinear Regression | 111 |

Experimental Designs for Regression | 118 |

Miscellaneous Topics in Regression | 126 |

Analysis of Real Data Sets | 127 |

Logistic Regression | 87 |