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Business Analytics by Ledolter
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Business Analytics by Ledolter
US $47.99US $47.99
Aug 30, 21:50Aug 30, 21:50
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Business Analytics by Ledolter

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    Item specifics

    Condition
    Good
    A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See all condition definitionsopens in a new window or tab
    Seller Notes
    “Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
    Book Title
    Business Analytics
    Topic
    Statistics
    Narrative Type
    Statistics
    Genre
    N/A
    Intended Audience
    N/A
    ISBN
    9781118447147

    About this product

    Product Identifiers

    Publisher
    Wiley & Sons, Incorporated, John
    ISBN-10
    111844714X
    ISBN-13
    9781118447147
    eBay Product ID (ePID)
    5038456613

    Product Key Features

    Number of Pages
    368 Pages
    Language
    English
    Publication Name
    Data Mining and Business Analytics with R
    Subject
    Programming Languages / General, Probability & Statistics / General, Databases / Data Mining, Statistics
    Publication Year
    2013
    Type
    Textbook
    Subject Area
    Mathematics, Computers, Business & Economics
    Author
    Johannes Ledolter
    Format
    Hardcover

    Dimensions

    Item Height
    1 in
    Item Weight
    24.1 Oz
    Item Length
    9.3 in
    Item Width
    6.2 in

    Additional Product Features

    Intended Audience
    Scholarly & Professional
    LCCN
    2013-000330
    Dewey Edition
    23
    Reviews
    "I first taught a Ph.D. level course in business applications of data mining 10 years ago. I regularly search the web, looking for business-oriented data mining books, and this is the first one I have found that is suitable for an MS in business analytics. I plan to use it. Anyone who teaches such a class and is inclined toward R should consider this text." ( Journal of the American Statistical Association , 1 January 2014)
    Illustrated
    Yes
    Dewey Decimal
    006.312
    Synopsis
    Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: - A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools - Illustrations of how to use the outlined concepts in real-world situations - Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials - Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences., Showcases R's critical role in the world of business Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible robust computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools Illustrations of how to use the outlined concepts in real-world situations Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences., Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets., Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents: A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools Illustrations of how to use the outlined concepts in real-world situations Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials Numerous exercises to help readers with computing skills and deepen their understanding of the material Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences.
    LC Classification Number
    QA76.9.D343L44 2013

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