R by example : concepts to code
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 r...
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| Auteurs principaux: | , , |
|---|---|
| 格式: | Livre numérique |
| 语言: | Anglais |
| 出版: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2012. |
| 丛编: | Use R!
|
| 主题: | |
| 在线阅读: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 提示: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • R by example, Jim Albert, Maria Rizzo, New York, Springer, 2012, 1 vol. (XIII-359 p.), Use R!, 978-1-4614-1364-6 • R by example, Jim Albert, Maria Rizzo, New York, Springer, 2012, 1 vol. (XIII-359 p.), Use R!, 978-1-4614-1364-6 • R by Example, Texte imprimé, 9781461413660 |
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| 100 | 1 | |a Albert, Jim, |d 1953- | |
| 245 | 1 | 0 | |a R by example : |b concepts to code |c by Jim Albert, Maria Rizzo. |
| 250 | |a 1st ed. 2012. | ||
| 260 | |a New York, NY : |b Springer New York. | ||
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| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Introduction Quantitative Data Categorical Data Presentation Graphics Exploratotry Data Analysis Basic Inference Models Regression Analysis of Variance I Analysis of Variance II Randomiczation tests Simulation Experiments Bayesian Modeling Monte Carlo Methods | |
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| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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 | ||
| 630 | |a R |n logiciel | ||
| 650 | |a Statistique mathématique |x Informatique | ||
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