Exploratory data analysis using R / created by Ronald K. Pearson.

By:

Pearson, Ronald K, 1952- [author.]

Material type: Text

TextSeries: Chapman & Hall/CRC data mining and knowledge discovery ; 45.Publisher: CRC Press/Taylor & Francis Group, 2018Description: xiii, 547 pages : illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781138480605 (hardback : acidfree paper)

Subject(s):

LOC classification:

QA76.9.D343 PEA

Contents:

Data, exploratory analysis, and R Graphics in R Exploratory data analysis: a first look Working with external data Linear regression models Crafting data stories Programming in R Working with text data Exploratory data analysis: a second look More general predictive models Keeping it all together

Summary: "This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of using R to do EDA. Based on the author's course at the University of Connecticut, the book assumes no prior exposure to data analysis or programming, and is designed to be as non-mathematical as possible. Exercises are included throughout, and a Solutions Manual will be available. The author will also provide a supplemental R package through the Comprehensive R Archive Network that will include implementations of some of the features in this book, along with data examples, tools, and datasets"--

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Book	Main Library Open Shelf	QA76.9.D34 PEA (Browse shelf(Opens below))	158346	Available		BK145826
Book	Main Library Open Shelf	QA76.9.D34 PEA (Browse shelf(Opens below))	15347	Available		BK145838

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Includes bibliographical references and index.

Data, exploratory analysis, and R
Graphics in R
Exploratory data analysis: a first look
Working with external data
Linear regression models
Crafting data stories
Programming in R
Working with text data
Exploratory data analysis: a second look
More general predictive models
Keeping it all together

"This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of using R to do EDA. Based on the author's course at the University of Connecticut, the book assumes no prior exposure to data analysis or programming, and is designed to be as non-mathematical as possible. Exercises are included throughout, and a Solutions Manual will be available. The author will also provide a supplemental R package through the Comprehensive R Archive Network that will include implementations of some of the features in this book, along with data examples, tools, and datasets"--

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