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"Statistik; Statistik matematika; Indication"

"APPLIED REGRESSION ANALYSIS focuses on the application of regression to real data and examples while employing commercial statistical and spreadsheet software. Designed for both business/economics undergraduates and MBAs, this text provides all of the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis. While only a prior introductory statistics course is required, a review of all necessary basic statistics is provided in chapter 2. The text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets."

""This is a concise account of certain topics in numerical analysis which a student is expected to know when he reaches an advanced course yet may not have been introduced to in his first course on the subject...This book is organized around the notion of error. After the concepts of stability and ill-conditioning (important in gauging the effects of all kinds of error) are elucidated in a first part of the book, discretization error, convergence error, and rounding error are each studied separately in a few important situations in the last three parts of the book. A review chapter on the Jordan canonical form and on norms for vectors and matrices precedes all." -- Mathematics of Computation, July 1973, page 669. "An excellent textbook at the advanced undergraduate or beginning graduate level dealing mainly with questions of stability and growth of error. . . . . . . There are a number of books available whose content intersects significantly with Ortega's material. . . . . However, Ortega's approach is somewhat different, utilizing the concepts of stability and error growth as they arise in various computational areas to unify the treatment, rather than separately dealing with the solution of linear systems, the eigenproblem, or differential equations." -- Choice, January 1973, page 331. "The selection of the material, its presentation with many examples, and, in particular, counterexamples, make this book extremely valuable--not only for students." -- G. Mayer, Zentrablatt fur Mathematik, 1990."

"This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital."