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The Prediction Matrix.<br> <br> Role of Variables in a Regression Equation.<br> <br> Effects of an Observation on a Regression Equation.<br> <br> Assessing the Influence of Multiple Observations.<br> <br> Joint Impact of a Variable and an Observation.<br> <br> Assessing the Effect of Errors of Measurements.<br> <br> A Study of Model Sensitivity by the Generalized Linear ModelApproach.<br> <br> Computational Considerations.<br> <br> Appendix: Summary of Vector and Matrix Norms, Proofs of ThreeTheorems.<br> <br> Refernces.<br> <br> Index.

<p><b>SAMPRIT CHATTERJEE, PhD,</b> is Professor Emeritus of Statistics at New York University. A Fellow of the American Statistical Association, Dr. Chatterjee has been a Fulbright scholar in both Kazhakstan and Mongolia. He is the coauthor of <i>Sensitivity Analysis in Linear Regression</i> and <i>A Casebook for a First Course in Statistics and Data Analysis,</i> both published by Wiley.</p> <p><b>ALI S. HADI, PhD,</b> is a Distinguished University Professor and former vice provost at the American University in Cairo (AUC). He is the founding Director of the Actuarial Science Program at AUC. He is also a Stephen H. Weiss Presidential Fellow and Professor Emeritus at Cornell University. Dr. Hadi is the author of four other books, a Fellow of the American Statistical Association, and an elected Member of the International Statistical Institute.</p>

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