Regression Using Jmp

Author : Iain Pardoe
Publisher : John Wiley & Sons
ISBN 13 : 1118345045
Total Pages : 372 pages
Book Rating : 4.47/5 ( download)

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Download or read book Applied Regression Modeling written by Iain Pardoe and published by John Wiley & Sons. This book was released on 2013-01-07 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.

Author : Rachel T. Silvestrini
Publisher : Quality Press
ISBN 13 : 0873899695
Total Pages : 468 pages
Book Rating : 4.97/5 ( download)

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Download or read book Linear Regression Analysis with JMP and R written by Rachel T. Silvestrini and published by Quality Press. This book was released on 2018-04-26 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive but low-cost textbook is intended for use in an undergraduate level regression course, as well as for use by practitioners. The authors have included some statistical details throughout the book but focus on interpreting results for real applications of regression analysis. Chapters are devoted to data collection and cleaning; data visualization; model fitting and inference; model prediction and inference; model diagnostics; remedial measures; model selection techniques; model validation; and a case study demonstrating the techniques outlined throughout the book. The examples throughout each chapter are illustrated using the software packages R and JMP. At the end of each chapter, there is a tutorial section demonstrating the use of both R and JMP. The R tutorial contains source code and the JMP tutorial contains a step by step guide. Each chapter also includes exercises for further study and learning.

Author : Jim Grayson
Publisher : SAS Institute
ISBN 13 : 1629599565
Total Pages : 358 pages
Book Rating : 4.64/5 ( download)

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Download or read book Building Better Models with JMP Pro written by Jim Grayson and published by SAS Institute. This book was released on 2015-08-01 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building Better Models with JMP® Pro provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts. It gives you the "what, why, and how" of using JMP® Pro for building and applying analytic models. This book is designed for business analysts, managers, and practitioners who may not have a solid statistical background, but need to be able to readily apply analytic methods to solve business problems. In addition, this book will greatly benefit faculty members who teach any of the following subjects at the lower to upper graduate level: predictive modeling, data mining, and business analytics. Novice to advanced users in business statistics, business analytics, and predictive modeling will find that it provides a peek inside the black box of algorithms and the methods used. Topics include: regression, logistic regression, classification and regression trees, neural networks, model cross-validation, model comparison and selection, and data reduction techniques. Full of rich examples, Building Better Models with JMP Pro is an applied book on business analytics and modeling that introduces a simple methodology for managing and executing analytics projects. No prior experience with JMP is needed. Make more informed decisions from your data using this newest JMP book.

Author : Ron Klimberg
Publisher : SAS Institute
ISBN 13 : 1629608017
Total Pages : 532 pages
Book Rating : 4.13/5 ( download)

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Download or read book Fundamentals of Predictive Analytics with JMP, Second Edition written by Ron Klimberg and published by SAS Institute. This book was released on 2017-12-19 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded second edition of Fundamentals of Predictive Analytics with JMP(R) bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. First, this book teaches you to recognize when it is appropriate to use a tool, what variables and data are required, and what the results might be. Second, it teaches you how to interpret the results and then, step-by-step, how and where to perform and evaluate the analysis in JMP . Using JMP 13 and JMP 13 Pro, this book offers the following new and enhanced features in an example-driven format: an add-in for Microsoft Excel Graph Builder dirty data visualization regression ANOVA logistic regression principal component analysis LASSO elastic net cluster analysis decision trees k-nearest neighbors neural networks bootstrap forests boosted trees text mining association rules model comparison With today’s emphasis on business intelligence, business analytics, and predictive analytics, this second edition is invaluable to anyone who needs to expand his or her knowledge of statistics and to apply real-world, problem-solving analysis. This book is part of the SAS Press program.

Author : Ian Cox
Publisher : SAS Institute
ISBN 13 : 1629590924
Total Pages : 308 pages
Book Rating : 4.29/5 ( download)

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Download or read book Discovering Partial Least Squares with JMP written by Ian Cox and published by SAS Institute. This book was released on 2013-10 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores Partial Least Squares and positions it within the more general context of multivariate analysis. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.

Author : John Sall
Publisher : Duxbury Resource Center
ISBN 13 : 9780534265656
Total Pages : 0 pages
Book Rating : 4.50/5 ( download)

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Download or read book JMP Start Statistics written by John Sall and published by Duxbury Resource Center. This book was released on 1996 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This complete data-analysis program combines outstanding graphics and amazing data analytics. JMP-IN's spreadsheets, data tables, and graphing capabilities are designed to help the student learn important statistics concepts while it handles all calculations.

Author : Trevor Bihl
Publisher : SAS Institute
ISBN 13 : 1635262410
Total Pages : 356 pages
Book Rating : 4.14/5 ( download)

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Download or read book Biostatistics Using JMP written by Trevor Bihl and published by SAS Institute. This book was released on 2017-10-03 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to solve biostatistical problems. Providing extensive breadth, from summary statistics to neural networks, this essential volume offers a comprehensive, step-by-step guide to using JMP to handle your data. The first biostatistical book to focus on software, Biostatistics Using JMP discusses such topics as data visualization, data wrangling, data cleaning, histograms, box plots, Pareto plots, scatter plots, hypothesis tests, confidence intervals, analysis of variance, regression, curve fitting, clustering, classification, discriminant analysis, neural networks, decision trees, logistic regression, survival analysis, control charts, and metaanalysis. Written for university students, professors, those who perform biological/biomedical experiments, laboratory managers, and research scientists, Biostatistics Using JMP provides a practical approach to using JMP to solve your biostatistical problems.

Author : Rudolf Jakob Freund
Publisher : SAS Press
ISBN 13 : 9781590471609
Total Pages : 0 pages
Book Rating : 4.01/5 ( download)

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Download or read book Regression Using JMP written by Rudolf Jakob Freund and published by SAS Press. This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

Author : Robert Carver
Publisher : SAS Institute
ISBN 13 : 1642956120
Total Pages : 510 pages
Book Rating : 4.22/5 ( download)

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Download or read book Practical Data Analysis with JMP, Third Edition written by Robert Carver and published by SAS Institute. This book was released on 2019-10-18 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the concepts and techniques of statistical analysis using JMP Practical Data Analysis with JMP, Third Edition, highlights the powerful interactive and visual approach of JMP to introduce readers to statistical thinking and data analysis. It helps you choose the best technique for the problem at hand by using real-world cases. It also illustrates best-practice workflow throughout the entire investigative cycle, from asking valuable questions through data acquisition, preparation, analysis, interpretation, and communication of findings. The book can stand on its own as a learning resource for professionals, or it can be used to supplement a college-level textbook for an introductory statistics course. It includes varied examples and problems using real sets of data. Each chapter typically starts with an important or interesting research question that an investigator has pursued. Reflecting the broad applicability of statistical reasoning, the problems come from a wide variety of disciplines, including engineering, life sciences, business, and economics, as well as international and historical examples. Application Scenarios at the end of each chapter challenge you to use your knowledge and skills with data sets that go beyond mere repetition of chapter examples. New in the third edition, chapters have been updated to demonstrate the enhanced capabilities of JMP, including projects, Graph Builder, Query Builder, and Formula Depot.

Author : Peter Goos
Publisher : John Wiley & Sons
ISBN 13 : 1119976162
Total Pages : 249 pages
Book Rating : 4.65/5 ( download)

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Download or read book Optimal Design of Experiments written by Peter Goos and published by John Wiley & Sons. This book was released on 2011-06-28 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.