Regression Using Jmp

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Overview

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.
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Product Details

  • ISBN-13: 9781590471609
  • Publisher: SAS Institute Inc.
  • Publication date: 6/11/2003
  • Edition description: New Edition
  • Pages: 288
  • Product dimensions: 7.50 (w) x 9.25 (h) x 0.60 (d)

Meet 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 degrees in mathematics education from North Carolina State University. His interest include the methods of teaching statistics and the applications of statistics to education measurement. Prior to working at SAS, Dr. Creighton taught high school and collegiate mathematics in North Carolina. He is coauthor of JMP® Start Statistics.

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Table of Contents

Acknowledgments
Using This Book
1 Regression Concepts 1
2 Regressions in JMP 25
3 Observations 73
4 Collinearity: Detection and Remedial Measures 105
5 Polynomial and Smoothing Models 139
6 Special Applications of Linear Models 175
7 Nonlinear Models 215
8 Regression with JMP Scripting Language 237
References 247
Index 249
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