Fundamentals of Predictive Analytics with JMP
(eBook)

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Published
SAS Institute, 2017.
Status
Available Online

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Format
eBook
Language
English
ISBN
9781629608013

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Citations

APA Citation, 7th Edition (style guide)

Ron Klimberg., Ron Klimberg|AUTHOR., & B. D. McCullough|AUTHOR. (2017). Fundamentals of Predictive Analytics with JMP . SAS Institute.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Ron Klimberg, Ron Klimberg|AUTHOR and B. D. McCullough|AUTHOR. 2017. Fundamentals of Predictive Analytics With JMP. SAS Institute.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Ron Klimberg, Ron Klimberg|AUTHOR and B. D. McCullough|AUTHOR. Fundamentals of Predictive Analytics With JMP SAS Institute, 2017.

MLA Citation, 9th Edition (style guide)

Ron Klimberg, Ron Klimberg|AUTHOR, and B. D. McCullough|AUTHOR. Fundamentals of Predictive Analytics With JMP SAS Institute, 2017.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work ID7214f883-bd3c-da54-abe8-88a82d04a97c-eng
Full titlefundamentals of predictive analytics with jmp
Authorklimberg ron
Grouping Categorybook
Last Update2023-06-08 20:00:45PM
Last Indexed2024-04-18 01:05:41AM

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First LoadedMay 8, 2023
Last UsedSep 12, 2023

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    [synopsis] => 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.
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