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R by example

Albert, Jim.

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R by example

Record Type:	Electronic resources : Monograph/item
Title/Author:	R by example/ by Jim Albert, Maria Rizzo.
Author:	Albert, Jim.
other author:	Rizzo, Maria L.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xv, 454 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Quantitative Data -- Categorical Data -- Exploratory Data Analysis -- Presentation Graphics -- Importing Data -- Basic Inference Models -- Regression -- Analysis of Variance I -- Analysis of Variance II -- Randomization Tests -- Multivariate Data -- Simulation Experiments -- Bayesian Modeling -- Monte Carlo Methods.
Contained By:	Springer Nature eBook
Subject:	R (Computer program language) -
Online resource:	https://doi.org/10.1007/978-3-031-76074-7
ISBN:	9783031760747

R by example
Albert, Jim.

R by example[electronic resource] /by Jim Albert, Maria Rizzo. - Second edition. - Cham :Springer Nature Switzerland :2024. - xv, 454 p. :ill., digital ;24 cm. - Use R!,2197-5744. - Use R!..

Introduction -- Quantitative Data -- Categorical Data -- Exploratory Data Analysis -- Presentation Graphics -- Importing Data -- Basic Inference Models -- Regression -- Analysis of Variance I -- Analysis of Variance II -- Randomization Tests -- Multivariate Data -- Simulation Experiments -- Bayesian Modeling -- Monte Carlo Methods.

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.

ISBN: 9783031760747

Standard No.: 10.1007/978-3-031-76074-7doiSubjects--Topical Terms:

784593
R (Computer program language)

LC Class. No.: QA276.45.R3

Dewey Class. No.: 519.5028553

R by example
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245 1 0 $a R by example $h [electronic resource] / $c by Jim Albert, Maria Rizzo.
250 $a Second edition.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xv, 454 p. : $b ill., digital ; $c 24 cm.
490 1 $a Use R!, $x 2197-5744
505 0 $a Introduction -- Quantitative Data -- Categorical Data -- Exploratory Data Analysis -- Presentation Graphics -- Importing Data -- Basic Inference Models -- Regression -- Analysis of Variance I -- Analysis of Variance II -- Randomization Tests -- Multivariate Data -- Simulation Experiments -- Bayesian Modeling -- Monte Carlo Methods.
520 $a 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.
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650 2 4 $a Probability and Statistics in Computer Science. $3 891072
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Coding and Information Theory. $3 891252
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