Summary: Kutner, Nachtsheim, Neter, Wasserman, Applied Linear Regression Models, 4/e (ALRM4e) is the long established leading authoritative text and reference on regression (previously Neter was lead author.) For students in most any discipline where statistical analysis or interpretation is used, ALRM has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented in a ...show moreprecise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in any discipline. ALRM 4e provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. Edition/Copyright: 4TH 04
New to This Edition
- Thoroughly Updated to include the latest developments and methods in statistics such as: multi-category (polytomous) logistic regression for nominal and ordinal data, expanded treatment of diagnostics for logistic regression, Akaike's Information Criterion and Schwarz's Bayesian Criterion for model selection, a more powerful Levene test, advanced bootstrapping, inclusion of data mining techniques such as neural networks and regression trees, and more, these updates assure that students are efficient at the most current statistical tools available.
- Improved Organization by combining related chapters and improving transitions between concepts this revision reflects a more useful organization making it easier for instructors to teach from and students to learn.
- Cases, Datasets and Examples Improved cases have been added to assignment material, with examples from finance, data sets have been updated and now include larger data sets. These changes provide an effective "business" perspective exposing students to relevant uses of regression techniques in business today.
- Enhanced integration of computing and automated methods now reflects a more current approach to implementing these techniques. This integration is included without sacrificing statistical literacy.
- Thorough, comprehensive coverage has come to be known as "the bible of statistics." Provides students with the most current and authoritative coverage available.
- Straightforward writing style, notation, and format for students in various disciplines, better preparing students for a wide range of jobs.
- Clean and reliable for teaching and handy reference students can use in their careers.
Publisher: McGraw-Hill Publishing Company