Regression Using JMP - Softcover

Rudolf J. Freund; Ramon C. Littell; Lee Creighton

Softcover

ISBN 10: 1590471601 ISBN 13: 9781590471609

Publisher: SAS Publishing, 2003

Synopsis

Filled with examples, Regression Using JMP introduces you to the basics of regression analysis using JMP software. You will learn how to perform regression analyses using a wide variety of models, including linear and nonlinear models. Taking a tutorial approach, the authors cover the customary Fit Y by X and Fit Model platforms, as well as the new features and capabilities of JMP Version 5. Output is covered in helpful detail. Thorough discussion of the following is also presented: confidence limits, examples using JMP scripting language, polynomial and smoothing models, regression in the context of linear model methodology, and diagnosis of and remedies for data problems including outliers and collinearity. Statistical consultants familiar with regression analysis and basic JMP concepts will appreciate the conversational, "what to look for" and "what if" scenarios presented. Non-statisticians with a working knowledge of statistical concepts will learn how to use JMP successfully for data analysis.

About this title

About the Author

Rudolf J. Freund, Ph.D., former associate director and cofounder of the Department of Statistics at Texas A&M University, is now professor emeritus. Dr. Freund received an M.A. degree in economics from the University of Chicago in 1951 and a Ph.D. in statistics from North Carolina State College in 1955. He has coauthored several impressive books, including SAS System for Regression, Third Edition; Regression Methods; SAS System for Linear Models, Third Edition; Statistical Methods; and Regression Analysis. Dr. Freund has been a SAS user since 1972 and is a former SUGI chairman.

Ramon C. Littell, Ph.D., is professor of statistics at the University of Florida, where he teaches applied statistics and serves as consulting statistician in the Institute of Food and Agricultural Sciences. Dr. Littell is coauthor of SAS¨ System for Regression, Third Edition; SAS¨ System for Linear Models, Third Edition; SAS¨ System for Mixed Models; and SAS System for Elementary Statistical Analysis, Second Edition. He is also widely published in statistical and applied journals. A SAS user since 1972, Dr. Littell has served as SUGI chairman and is a Fellow of the American Statistical Association.

Lee Creighton, Ph.D., is the documentation manager for the JMP division at SAS Institute. He received his undergraduate and graduate degrees in mathematics education from North Carolina State University. His interests include the methods of teaching statistics and the applications of statistics to educational measurement. Prior to working at SAS, Dr. Creighton taught high school and collegiate mathematics in North Carolina. He is coauthor of JMP Start Statistics.

Review

Like all of the JMP documentation, I found Regression Using JMP by Freund, Littell, and Creighton to be well written and helpful. I found the chapter on collinearity to be particularly useful, as it explained the use of leverage plots to explore collinearity in a clear, straightforward manner. I also found the technical support over the phone to be particularly helpful in explaining some of the concepts in the book. --Rob Gier, Medication Delivery, Baxter Healthcare Corporation

The text provides a great introduction to JMP linear and nonlinear regression models. The examples of the models used provide the framework for many of the commonly used multivariate statistical methods, multiple regression, analysis of variance, analysis of covariance for continuous response data, and logistic regression for binary data. The basic fundamentals of regression diagnostics are illustrated at a very elementary level with detailed explanations. The examples in the text are very applicable to various disciplines and very easy to understand and follow. Overall I would highly recommend this text to anyone in need of a manual in regression methods in JMP. --RLuis Rene Mateo, Research Statistician

Regression Using JMP is a well-written book for the intermediate-level statistician who wants to get more from the JMP program. The introductory chapter provides a solid review of basic regression theory. Matrix theory is often omitted from software-related books. It was a pleasant surprise to see it included. Matrix formulas are used throughout the book. Many subtle JMP features (regression related or not) are incorporated into the examples. I particularly liked the combination of JMP features used in the presentation of regression diagnostics--for example, blending the use of overlay plots, colors, and markers with the standard Fit Y by X tools. Most JMP texts and classes limit their presentations solely to the platform being presented. This book offers a better blend of theory and mechanics than most software-oriented texts. In the explanatory paragraphs, 'English descriptions of the parameters are regularly presented before proceeding with the more theoretical detail. They explain statistical assumptions, pitfalls, and how the newly introduced parameter relates to other terms. Overall, I would recommend this book to my fellow JMP users. --Eric Hamann, Wyeth, Principal Biostatistician

Edition details

• Publisher: SAS Publishing
• Publication date: 2003
• ISBN 10: 1590471601
• ISBN 13: 9781590471609
• Binding: Paperback
• Language: English
• Edition number: 1
• Number of pages: 288