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Edition originale
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Ajouter au panierSoft cover. Etat : Very Good. 1st Edition. Very good copy in softcover. Grey spine with white title.
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Ajouter au panierEtat : New.
Langue: anglais
Edité par Taylor & Francis Inc, Portland, 2018
ISBN 10 : 149873023X ISBN 13 : 9781498730235
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Ajouter au panierHardcover. Etat : new. Hardcover. Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" good, bad, and ugly features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data.The book begins with a detailed overview of data, exploratory analysis, and R, as well as graphics in R. It then explores working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. The book ends with a chapter on "keeping it all together" that includes managing the R installation, managing files, documenting, and an introduction to reproducible computing.The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. it keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available.About the Author:Ronald K. Pearson holds the position of Senior Data Scientist with GeoVera, a property insurance company in Fairfield, California, and he has previously held similar positions in a variety of application areas, including software development, drug safety data analysis, and the analysis of industrial process data. He holds a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and has published conference and journal papers on topics ranging from nonlinear dynamic model structure selection to the problems of disguised missing data in predictive modeling. Dr. Pearson has authored or co-authored books including Exploring Data in Engineering, the Sciences, and Medicine (Oxford University Press, 2011) and Nonlinear Digital Filtering with Python. He is also the developer of the DataCamp course on base R graphics and is an author of the datarobot and GoodmanKruskal R packages available from CRAN (the Comprehensive R Archive Network). "A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc." Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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Ajouter au panierUNK. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierEtat : New.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 75,70
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Ajouter au panierEtat : New. pp. 562.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierPaperback / softback. Etat : New. New copy - Usually dispatched within 4 working days.
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Ajouter au panierEtat : New. pp. 562.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
EUR 83,26
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Ajouter au panierEtat : New. pp. 562.
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierMixed media product. Etat : New. New copy - Usually dispatched within 4 working days.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 81,38
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Ajouter au panierBook/CD-ROM. Etat : Brand New. 547 pages. 9.00x6.00x1.00 inches. In Stock.
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
EUR 89,45
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Ajouter au panierEtat : New. pp. 562.
Vendeur : moluna, Greven, Allemagne
EUR 62,76
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Ajouter au panierEtat : New. Ronald K. Pearson currently works for GeoVera, a property insurance company in Fairfield, California, primarily in the analysis of text data. He holds a PhD in Electrical Engineering and Computer Science from the Massachussetts Institute.
Langue: anglais
Edité par Taylor & Francis Inc, Portland, 2018
ISBN 10 : 149873023X ISBN 13 : 9781498730235
Vendeur : AussieBookSeller, Truganina, VIC, Australie
EUR 88,75
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Ajouter au panierHardcover. Etat : new. Hardcover. Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" good, bad, and ugly features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data.The book begins with a detailed overview of data, exploratory analysis, and R, as well as graphics in R. It then explores working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. The book ends with a chapter on "keeping it all together" that includes managing the R installation, managing files, documenting, and an introduction to reproducible computing.The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. it keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available.About the Author:Ronald K. Pearson holds the position of Senior Data Scientist with GeoVera, a property insurance company in Fairfield, California, and he has previously held similar positions in a variety of application areas, including software development, drug safety data analysis, and the analysis of industrial process data. He holds a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and has published conference and journal papers on topics ranging from nonlinear dynamic model structure selection to the problems of disguised missing data in predictive modeling. Dr. Pearson has authored or co-authored books including Exploring Data in Engineering, the Sciences, and Medicine (Oxford University Press, 2011) and Nonlinear Digital Filtering with Python. He is also the developer of the DataCamp course on base R graphics and is an author of the datarobot and GoodmanKruskal R packages available from CRAN (the Comprehensive R Archive Network). "A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc." Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Langue: anglais
Edité par Taylor & Francis Ltd Jun 2020, 2020
ISBN 10 : 0367571560 ISBN 13 : 9780367571566
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 79,61
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware - Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of 'interesting' - good, bad, and ugly - features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data.
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
EUR 157,17
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Ajouter au panierHardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 211,42
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 222,63
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Ajouter au panierEtat : New.
Langue: anglais
Edité par Taylor & Francis Ltd, London, 2018
ISBN 10 : 1138480606 ISBN 13 : 9781138480605
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
EUR 224,99
Quantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" good, bad, and ugly features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to explore and explain data.The book begins with a detailed overview of data, exploratory analysis, and R, as well as graphics in R. It then explores working with external data, linear regression models, and crafting data stories. The second part of the book focuses on developing R programs, including good programming practices and examples, working with text data, and general predictive models. The book ends with a chapter on "keeping it all together" that includes managing the R installation, managing files, documenting, and an introduction to reproducible computing.The book is designed for both advanced undergraduate, entry-level graduate students, and working professionals with little to no prior exposure to data analysis, modeling, statistics, or programming. it keeps the treatment relatively non-mathematical, even though data analysis is an inherently mathematical subject. Exercises are included at the end of most chapters, and an instructor's solution manual is available.About the Author:Ronald K. Pearson holds the position of Senior Data Scientist with GeoVera, a property insurance company in Fairfield, California, and he has previously held similar positions in a variety of application areas, including software development, drug safety data analysis, and the analysis of industrial process data. He holds a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and has published conference and journal papers on topics ranging from nonlinear dynamic model structure selection to the problems of disguised missing data in predictive modeling. Dr. Pearson has authored or co-authored books including Exploring Data in Engineering, the Sciences, and Medicine (Oxford University Press, 2011) and Nonlinear Digital Filtering with Python. He is also the developer of the DataCamp course on base R graphics and is an author of the datarobot and GoodmanKruskal R packages available from CRAN (the Comprehensive R Archive Network). This textbook introduces exploratory data analysis (EDA) and covers the range of interesting features we can expect to find in data. The book also explores the practical mechanics of using R to do EDA. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 207,18
Quantité disponible : 10 disponible(s)
Ajouter au panierEtat : New.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 220,33
Quantité disponible : 3 disponible(s)
Ajouter au panierEtat : New.