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Handbook of Statistical Analysis and Data Mining Applications 1st Edition

4.1 out of 5 stars 52 ratings

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

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Handbook of Statistical Analysis
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Editorial Reviews

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)

Review

The essential professional reference for data mining applications and statistical analysis

Product details

  • Publisher ‏ : ‎ Academic Press
  • Publication date ‏ : ‎ June 5, 2009
  • Edition ‏ : ‎ 1st
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 864 pages
  • ISBN-10 ‏ : ‎ 0123747651
  • ISBN-13 ‏ : ‎ 978-0123747655
  • Item Weight ‏ : ‎ 3.65 pounds
  • Dimensions ‏ : ‎ 7.75 x 1.5 x 9.25 inches
  • Customer Reviews:
    4.1 out of 5 stars 52 ratings

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Customer reviews

4.1 out of 5 stars
52 global ratings

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Customers say

Customers find the book provides a good overview of data mining techniques with helpful examples. Moreover, they appreciate its ease of use, with one customer noting the step-by-step tutorials, and its readability, with one describing it as brilliantly written.

AI-generated from the text of customer reviews

16 customers mention "Knowledge level"16 positive0 negative

Customers appreciate the book's comprehensive coverage of data mining techniques and helpful examples, with one customer noting how it embeds these methods in a broader analytical context.

"...critical to successful analytics, the automation in KXEN is an effective adjunct and accelerator to the expression of the analyst's intellectual..." Read more

"...It promises many detailed examples and cases. The companion DVD has detailed cases and also has a real 90 day trial copy of Statistica...." Read more

"Good read, touches upon broader aspects of data mining without delving too much into the mathematics of it. Good for any one interested in Data mining" Read more

"...that leads to the need for data mining; I found this bit of history quite fascinating and enlightening; it is something I've found in few other data..." Read more

6 customers mention "Ease of use"6 positive0 negative

Customers find the book easy to follow, with one customer noting it includes step-by-step tutorials and another mentioning practical hands-on advice.

"...I found KXEN's ability to automate the process (and leverage a database engine!)..." Read more

"...prefer RapidMiner, a product that is amazingly feature-rich, so easy to use it is actually fun, supported by a robust open-source model, and..." Read more

"...Through tutorials and case studies, anyone from those just learning about data mining to experts will get great value from this book...." Read more

"...It is a good for review and exploration of methods to augment the methods that I am most familiar with...." Read more

3 customers mention "Readability"3 positive0 negative

Customers find the book easy to read, with one describing it as brilliantly written.

"...With e download text easy read on pc screen not certain would be good read on K." Read more

"...The best chapter is the one of Top 10 DM mistakes. This is brilliantly written and edited...." Read more

"Well written, easy read" Read more

Top reviews from the United States

  • Reviewed in the United States on February 11, 2010
    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.
    4 people found this helpful
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  • Reviewed in the United States on June 23, 2009
    This is one of the few, of many, data mining books that delivers what it promises. It promises many detailed examples and cases. The companion DVD has detailed cases and also has a real 90 day trial copy of Statistica. I have taught data mining for over 10 years and I know it is very difficult to find comprehensive cases that can be used for classroom examples and for students to actually mine data. The price of the book is also very reasonable expecially when you compare the quantity and quality of the material to the typical intro stat book that usually costs twice as much as this data mining book.
    The book also addresses new areas of data mining that are under development. Anyone that really wants to understand what data mining is about will find this book infinetly useful.
    9 people found this helpful
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  • Reviewed in the United States on March 14, 2014
    Good read, touches upon broader aspects of data mining without delving too much into the mathematics of it. Good for any one interested in Data mining
    One person found this helpful
    Report
  • Reviewed in the United States on June 3, 2010
    This book is for practitioners, not for those seeking a deeper understanding of data mining. It both makes and delivers on that claim. All major data mining topics are covered, though in a necessarily shallow manner in keeping with the book's goal of getting past the theory and moving to the practice.

    Oddly, the very start of the book does have a bit of theory in the form of the historical roots of statistics and the limitations of statistics that leads to the need for data mining; I found this bit of history quite fascinating and enlightening; it is something I've found in few other data mining books, and I've read several.

    The trouble is, I do like theory a bit. I have a master's in computer science, so I'm a bit biased that way, thus my relatively low scoring of the work.

    About 1/3rd of the book is dedicated to working through real problems, and that is the overwhelming strength of the book. If you are one who learns by doing rather than by theorizing, you'll find this book outstanding.

    The biggest criticism I have of the book is that it is clear that there are significant parts where the authors just didn't have their hearts in it; it felt like they wrote certain sections because the publisher told them they had to in order to hit some type of target marketing segment.

    It's also unfortunate that all three software products provided expire in 90 days or less. I'm never one to accomplish anything in 90 days, let alone get through a 700-page technical work!!! I know they are the 3 top mining tools, but I much prefer RapidMiner, a product that is amazingly feature-rich, so easy to use it is actually fun, supported by a robust open-source model, and free.

    Overall, a solid work. But to me, theory matters, that's one star down; and rigorous, enthusiastic writing matters, so that's two stars down. In the 3-stars that remain is lots of hands-on practice if you don't mind expiring software, and for that it is very strong.
    75 people found this helpful
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  • Reviewed in the United States on March 12, 2010
    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.
    6 people found this helpful
    Report
  • Reviewed in the United States on June 27, 2009
    I had experience with many of the statistical tools that fall under the heading of data mining. There are good books on GAMs and so on. What I like about this book is that it embeds those methods in a broader context, that of the philosophy and structure of data mining writ large, especially as the methods are used in the corporate world. To me, it was really helpful in thinking like a data miner, especially as it involves the mix of science and art.

    I also had no experience with Statistica Data Miner but have been very impressed with the program relative to those that are less well documented (WEKA) and too darned expensive (SAS EM)

    The richness of the examples is so helpful.
    14 people found this helpful
    Report
  • Reviewed in the United States on August 23, 2010
    I thought from its title that this book not only comes with real world applications but also introduces basic concepts and theory behind these data mining algorithms. I was not asking for in-depth explanation for these algorithms but at least, it has to be able to make us comfortable with these methods. However, after reading these algorithms covered in this book, I still have no idea how these algorithms work and what is the best way to approach different methods. Certainly a big dissapointment for me!
    23 people found this helpful
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Top reviews from other countries

  • Invoice
    5.0 out of 5 stars Five Stars
    Reviewed in the United Kingdom on March 16, 2017
    brilliant material
  • Trading Central
    5.0 out of 5 stars Eureka! Finally Datamining Reference for the Practitioner
    Reviewed in Canada on September 28, 2013
    It seems rare to find an actual book that lives up to it's description given by the authors as to the content and what can be expected when it comes to datamining topics. Generally the academic reviews are biased and favorable giving the practitioner a book that will be filled with proofs and formulas with little else to begin the implementation process.

    This book comes as advertised, a handbook with practical explanations of techniques coupled with references to software that will give a "good enough" solution to a finance problem.

    Others may complain that the book in fact is software specific but the topic area will require the use of sophisticated software and a supporting team to be of any value in the enterprise setting.

    For the lone wolf the book still provides enough of an overview of the topic areas to allow the reader to be familiar with the buzzwords and concepts used to begin the process.

    The authors have also kept the chapters short enough providing enough clarity in a few words without the clutter of academic textbook approaches that come with detailed bibliographies and references to obscure works that the practitioner has either no interest or desire to read as justification for the point being made.

    As a reference book, this is the one that should be on the desk of the practitioner who can refer to it when the young gun who stumbles into the office speaking in incomprehensible terms that can easily confuse the manager and lead to lost time and effectiveness in presenting the findings given by the intern hired for the summer.

    Nice to know that there are still writers with impeccable academic backgrounds writing books giving applied solutions for managers within a framework that uses generally available software packages as the learning vehicle.

    Must have reference for the analytics and datamining field's that will play much greater roles in finance and business decision making.
  • Mark S
    1.0 out of 5 stars Needs serious editing
    Reviewed in the United Kingdom on October 26, 2017
    Far too long and repetitive.