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Handbook of Statistical Analysis and Data Mining Applications, by John Elder IV
Ebook Free Handbook of Statistical Analysis and Data Mining Applications, by John Elder IV
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The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions.
- Written "By Practitioners for Practitioners"
- Non-technical explanations build understanding without jargon and equations
- Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models using Statistica, SAS and SPSS software
- Practical advice from successful real-world implementations
- Includes extensive case studies, examples, MS PowerPoint slides and datasets
- CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book
- Sales Rank: #108310 in Books
- Published on: 2009-06-05
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.50" w x 7.60" l, 3.60 pounds
- Binding: Hardcover
- 864 pages
Review
"I strongly resonated to the Top 10 Data Mining mistakes.... There is a wealth of material in this handbook that will repay study."
- Peter Lachenbruch, Oregon State U., Past President, American Statistical Society (from Foreword 1)
Data mining practitioners, here is your bible, the complete "driver's manual" for data mining. From starting the engine to handling the curves, this book covers the gamut of data mining techniques - including predictive analytics and text mining - illustrating how to achieve maximal value across business, scientific, engineering and medical applications. What are the best practices through each phase of a data mining project? How can you avoid the most treacherous pitfalls? The answers are in here.
Going beyond its responsibility as a reference book, this resource also provides detailed tutorials with step-by-step instructions to drive established data mining software tools across real world applications. This way, newcomers start their engines immediately and experience hands-on success.
If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner.
- Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World
"Great introduction to the real-world process of data mining. The overviews, practical advise, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners."
-- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)
... a valuable resource... The book's straightforward style--it presents intuitive explanations and avoids rigorous mathematical formulations--makes difficult concepts accessible to a broad audience.-ACM Computing Reviews
"...an exceptional book that should be on every data miner's bookshelf, or better yet, found lying open next to the computer."
Dean Abbott, Abbott Analytics --from Foreword 2
"...If you want to roll-up your sleeves and execute on predictive analytics, this is your definite, go-to resource. To put it lightly, if this book isn't on your shelf, you're not a data miner."
- Eric Siegel, Ph.D., President, Prediction Impact, Inc. and Founding Chair, Predictive Analytics World
“Great introduction to the real-world process of data mining. The overviews, practical advice, tutorials, and extra CD material make this book an invaluable resource for both new and experienced data miners.”
-- Karl Rexer, PhD (President & Founder of Rexer Analytics, Boston, Massachusetts)
From the Back Cover
Tutorials employ leading software tools including STATISTICA Data Miner, SPSS Clementine, and SAS Enterprise Miner -- and show practitioners how to solve real-world data mining challenges in a wide variety of fields, including sales, medical diagnosis, finance, aviation engineering, marketing, banking, pharmaceutical discovery, industrial control, weather forecasting, clinical psychology, ecology, astronomy, and social networks.
This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build practical solutions. Using the methods of this book produces new KNOWLEDGE that facilitates DECISIONS which lead to ACTIONS that result in SUCCESS.
About the Author
Robert Nisbet, John Elder, and Gary Miner have been University professors (in Biology, Engineering, and Medicine, respectively) and are skilled at making complex topics understandable. But what makes this book so unique and useful is their combined century of experience in industry -- where making analytic techniques work on an astonishing array of challenges has saved their clients and sponsors tens of millions of dollars.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Great hands on primer!
By Stephen C. Knutson
Nisbet's, Elder's and Miner's book on statistical analysis, was effective in that it:
- gave a intellectual insight into the thinking world of the analyst, as well as
- defined a strong analytics process to follow and
- gave you hands on examples and tool discussions that attempt to implement the intellectual concepts and process.
In the cases of KXEN and SPSS's Clementine. I was able to download their trial software and use this book to exercise the concepts.
I found KXEN's ability to automate the process (and leverage a database engine!) and do much of the analytics at the "click of a button" very powerful, reinforcing much of the book.
It is clear that the "thinking" part of analytics is still important and critical to successful analytics, the automation in KXEN is an effective adjunct and accelerator to the expression of the analyst's intellectual thinking.
0 of 0 people found the following review helpful.
half of the book is about a tool (Statistica) that it makes the book sound like a Sales-y book
By Eric Franchomme
not really worth the price. half of the book is about a tool (Statistica) that it makes the book sound like a Sales-y book. the first part of the book is just fine; I enjoyed more "Data science for business" as an introduction book. "Statistical analysis and data mining" does not fit as an introduction book nor as an advanced book.
5 of 5 people found the following review helpful.
Very helpful includes useful tutorials
By David Lehmann
discussion proceeds in logical way- start by working one example then go back and get your questions answered. trail software download no problems. highly recommend but must buy hardcopy to get dvd. dvd not included in e download. Amazon very quick to help me cancel e download and order hardcopy once i became aware the content of the dvd not included in e download. complements to author and thanks to Amazon for working problem. With e download text easy read on pc screen not certain would be good read on K.
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