Exploring Data Science with R and the Tidyverse: A Concise Introduction by Jerry

Description: Exploring Data Science with R and the Tidyverse by Jerry Bonnell, Mitsunori Ogihara This book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows. FORMAT Hardcover CONDITION Brand New Publisher Description This book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows without needing to reference extensive amounts of external resources for onboarding. The contents are targeted for undergraduate students but are equally applicable to students at the graduate level and beyond. The book develops concepts using many real-world examples to motivate the reader. Upon completion of the text, the reader will be able to: Gain proficiency in R programming Load and manipulate data frames, and "tidy" them using tidyverse tools Conduct statistical analyses and draw meaningful inferences from them Perform modeling from numerical and textual data Generate data visualizations (numerical and spatial) using ggplot2 and understand what is being representedAn accompanying R package "edsdata" contains synthetic and real datasets used by the textbook and is meant to be used for further practice. An exercise set is made available and designed for compatibility with automated grading tools for instructor use. Author Biography Jerry Bonnell is a Ph.D. candidate in Computer Science at the University of Miami, and a University of Miami Fellow. His research areas include Machine Learning and Natural Language Processing. His research targets domain experts in Digital Humanities (DH) and is shown in publications in Digital Scholarship in the Humanities, Digital Humanities Quarterly, and the ACL Special Interest Group on Language Technologies for the Socio-Economic Sciences and Humanities (LaTeCH-CLfL). He also teaches the undergraduate-level course "Data Science for the World" at the University of Miami. Mitsunori Ogihara is a Professor of Computer Science at the University of Miami, Coral Gables, Florida, USA, and is the Director of its Master of Science in Data Science program. He received his Ph.D. in Information Sciences from Tokyo Institute of Technology, Tokyo, Japan. He is an author/co-author/co-editor of four books and has published more than 200 peer-reviewed journals and conference papers. He serves on the editorial board for a few academic journals, including Theory of Computing Systems, Springer, for which he is the Editor-in-Chief. Table of Contents 1. Data Types 2. Data Transformation 3. Data Visualization 4. Building Simulations 5. Sampling 6. Hypothesis Testing 7. Quantifying Uncertainty 8. Towards Normality 9. Regression 10. Text Analysis Details ISBN1032329505 Author Mitsunori Ogihara Publisher Taylor & Francis Ltd Year 2023 ISBN-13 9781032329505 Format Hardcover Subtitle A Concise Introduction Place of Publication London Illustrations 1 Tables, color; 8 Tables, black and white; 158 Line drawings, color; 42 Line drawings, black and white; 158 Illustrations, color; 42 Illustrations, black and white ISBN-10 1032329505 Publication Date 2023-08-14 AU Release Date 2023-08-14 NZ Release Date 2023-08-14 UK Release Date 2023-08-14 Pages 476 Alternative 9781032341705 DEWEY 006.312 Audience Tertiary & Higher Education Imprint Chapman & Hall/CRC US Release Date 2023-08-14 Country of Publication United Kingdom We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159583889;

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