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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, authors Rudolf Freund, Ramon Littell, and Lee Creighton 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.
|Using This Book|
|2||Regressions in JMP||25|
|4||Collinearity: Detection and Remedial Measures||105|
|5||Polynomial and Smoothing Models||139|
|6||Special Applications of Linear Models||175|
|8||Regression with JMP Scripting Language||237|