Librería: Jackson Street Booksellers, Omaha, NE, Estados Unidos de America
Original o primera edición
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Añadir al carritoSoft cover. Condición: Very Good. 1st Edition. Very good copy in softcover. Grey spine with white title.
Librería: Zoom Books Company, Lynden, WA, Estados Unidos de America
EUR 66,47
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Idioma: Inglés
Publicado por Taylor & Francis Inc, Portland, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 74,19
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Añadir al carritoHardcover. Condición: 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.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 71,81
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Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Taylor and Francis Inc, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 67,46
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Añadir al carritoUNK. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 73,37
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 66,33
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Idioma: Inglés
Publicado por Taylor & Francis Group, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: Majestic Books, Hounslow, Reino Unido
EUR 80,72
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Añadir al carritoCondición: New. pp. 562.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 73,28
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Idioma: Inglés
Publicado por Taylor & Francis Group, 2020
ISBN 10: 0367571560 ISBN 13: 9780367571566
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 89,02
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Añadir al carritoCondición: New. pp. 562.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 66,85
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Taylor & Francis Group, 2020
ISBN 10: 0367571560 ISBN 13: 9780367571566
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 84,25
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Añadir al carritoCondición: New. pp. 562.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 73,89
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Añadir al carritoMixed media product. Condición: New. New copy - Usually dispatched within 4 working days.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 81,61
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Añadir al carritoBook/CD-ROM. Condición: Brand New. 547 pages. 9.00x6.00x1.00 inches. In Stock.
Idioma: Inglés
Publicado por Taylor & Francis Group, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 102,80
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Añadir al carritoCondición: New. pp. 562.
Idioma: Inglés
Publicado por Taylor & Francis Group, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 97,38
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Añadir al carritoCondición: New. pp. 562.
Librería: moluna, Greven, Alemania
EUR 68,02
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Añadir al carritoCondición: 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.
Idioma: Inglés
Publicado por Taylor & Francis Inc, Portland, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 89,66
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Añadir al carritoHardcover. Condición: 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.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 128,38
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Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Taylor & Francis Ltd Jun 2020, 2020
ISBN 10: 0367571560 ISBN 13: 9780367571566
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 86,09
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Añadir al carritoTaschenbuch. Condición: 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.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 153,91
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 142,65
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Librería: HPB-Red, Dallas, TX, Estados Unidos de America
EUR 159,67
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Añadir al carritoHardcover. Condición: 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!
EUR 152,13
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
EUR 119,08
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Añadir al carritoCondición: New. Ronald K. Pearson holds a PhD in Electrical Engineering and Computer Science from the Massachussetts Institute of Technology and has more than 40 years professional experience in exploratory data analysis. Dr. Pearson has held industrial, business.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 190,86
Cantidad disponible: 10 disponibles
Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.