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03166aam a2200421 i 4500 001 8A671CCA72D911EDA0B05B7C49ECA4DB 003 SILO 005 20221203010154 008 211127t20222022flua b 001 0 eng 010 $a 2021054754 020 $a 0367524686 020 $a 9780367524685 020 $a 0367532174 020 $a 9780367532178 035 $a (OCoLC)1284981269 040 $a LBSOR/DLC $b eng $e rda $c DLC $d OCLCO $d OCLCF $d OCLCO $d YDX $d SILO 042 $a pcc 050 00 $a QA276.45 R3 T56 2022 100 1 $a Timbers, Tiffany-Anne, $e author. 245 10 $a Data science : $b a first introduction / $c Tiffany Timbers, Trevor Campbell, Melissa Lee. 250 $a First edition. 264 1 $a Boca Raton : $b CRC Press, Taylor & Francis Group, $c 2022. 300 $a xxi, 420 pages : $b illustrations (chiefly color) ; $c 27 cm. 490 1 $a Chapman & Hall/CRC data science series 504 $a Includes bibliographical references and index. 505 0 $a R and the tidyverse -- Reading in data locally and from the Web -- Cleaning and wrangling data -- Effective data visualization -- Classification I : training & predicting -- Classification II : evaluation & tuning -- Regression I : K-nearest neighbors -- Regression II : linear regression -- Clustering -- Statistical inference -- Combining code and text rwith Jupyter -- Collaboration with version control -- Setting up your computer. 520 $a "Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models. Based on sound educational research and active learning principles, the book uses a modern approach to the R programming language and accompanying sheets for self-directed learning this book will leave students well-prepared for data science projects. Data Science: An Introduction focuses on workflows and communication strategies that are clear, reproducible, and shareable. Aimed at first year undergraduates with only minimal prior knowledge of mathematics and programming this book is suitable for students across many disciplines. All source code is available online as a GitHub repository, demonstrating the use of good reproducible and clear project workflows and is also accompanied by autograded Jupyter worksheets, providing the reader with guided interactive instruction"-- $c Provided by publisher. 650 0 $a Mathematical statistics $x Data processing $v Textbooks. 650 0 $a R (Computer program language) $v Textbooks. 650 0 $a Quantitative research $x Data processing $v Textbooks. 700 1 $a Campbell, Trevor $c (Professor of statistics), $e author. 700 1 $a Lee, Melissa $c (Statistics educator), $e author. 776 08 $i Online version: $a Timbers, Tiffany-Anne. $t Data science. $b First edition $d Boca Raton : CRC Press, 2022 $z 9781003080978 $w (DLC) 2021054755 830 0 $a Chapman & Hall/CRC data science series. 941 $a 1 952 $l USUX851 $d 20240202024337.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=8A671CCA72D911EDA0B05B7C49ECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search