R by example

By:

Albert, Jim

Contributor(s):

Rizzo, Maria [Co-author]

Series: User R !Publication details: Cham: Springer, 2024.Edition: 2nd edDescription: xv, 454 p.: col. ill.; pbk.: 24 cmISBN:

9783031760730

Subject(s):

DDC classification:

519.50285 ALB

Summary: Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R. The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods. https://link.springer.com/book/10.1007/978-3-031-76074-7

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	IIT Gandhinagar	General	519.50285 ALB (Browse shelf(Opens below))	1	Available	036414

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Includes References and Index

Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.

The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.

The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods.

https://link.springer.com/book/10.1007/978-3-031-76074-7

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