Regression Using JMP / Edition 1

Regression Using JMP / Edition 1

by Rudolf Freund, Lee Creighton, Ramon Littell
     
 

ISBN-10: 0471483079

ISBN-13: 9780471483076

Pub. Date: 08/22/2003

Publisher: Wiley

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 author cover the customary Fit Y by X and Fit Model platforms, as well as the new features and

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 author 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

• polynomial and smoothing models

• examples using JMP scripting language

• regression in the context of linear model methodology

• diagnosis of and remedies for data problems including outliers and collinearity

Statistical consultants familiar with regression analysis and with 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 to use JMP successfully for each analysis.

Product Details

ISBN-13:
9780471483076
Publisher:
Wiley
Publication date:
08/22/2003
Series:
Wiley-Sas(R) Publication Ser.
Edition description:
New Edition
Pages:
288
Product dimensions:
7.52(w) x 9.02(h) x 0.53(d)

Table of Contents

Acknowledgments.

Using This Book.

1. Regression Concepts.

2. Regressions in JMP.

3. Observations.

4. Collinearity: Detection and Remedial Measures.

5. Polynomial and Smoothing Models.

6. Special Applications of Linear Models.

7. Nonlinear Models.

8. Regression with JMP Scripting Language.

References.

Index.

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