Soft cover. Zustand: Very Good. 1st Edition. Very good copy in softcover. Grey spine with white title.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition.
Sprache: Englisch
Verlag: Taylor & Francis Inc, Portland, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: 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.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New.
Anbieter: GreatBookPrices, Columbia, MD, USA
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Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
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In den WarenkorbUNK. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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In den WarenkorbZustand: New. pp. 562.
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In den WarenkorbPaperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. pp. 562.
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In den WarenkorbZustand: 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.
Sprache: Englisch
Verlag: Taylor & Francis Inc, Portland, 2018
ISBN 10: 149873023X ISBN 13: 9781498730235
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Hardcover. Zustand: 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.
Sprache: Englisch
Verlag: Taylor & Francis Ltd Jun 2020, 2020
ISBN 10: 0367571560 ISBN 13: 9780367571566
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Hardcover. Zustand: 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!
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, London, 2018
ISBN 10: 1138480606 ISBN 13: 9781138480605
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: 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.
Anbieter: GreatBookPrices, Columbia, MD, USA
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Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: New. New. book.
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EUR 208,83
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