R by Example
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Beschreibung
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, this book 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.
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, this book 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.
Illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics Provide a general introduction to the R system and provides an overview of the capabilities of R to perform basic numerical and graphical summaries of data R functions are presented in the context of interesting applications with real data
Autor*in
Jim Albert
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From the reviews:
“This book is an example-driven introduction to both R as a programming environment and widely used statistical concepts such as regression, ANOVA, Bayesian modeling, and randomization and simulation experiments. … The book is an excellent addition to the lecture notes for undergraduate and master students as well as a reliable source of examples for lecturers. The exercises presented in parallel with the theoretical aspects guide the reader in an efficient way through the statistical methods.” (Irina Ioana Mohorianu, zbMATH, Vol. 1275, 2014)()