- 412 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
About this book
R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered.
- Addresses data examples that can be downloaded directly from the R website
- No other source is needed to gain practical experience
- Focus on the essentials in graphical outlays
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Computational Statistics with R by in PDF and/or ePUB format, as well as other popular books in Matemáticas & Probabilidad y estadística. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Preface
- Chapter 1: Introduction to R
- Chapter 2: R Graphics
- Chapter 3: Graphics Miscellanea
- Chapter 4: Matrix Algebra Topics in Statistics and Economics Using R
- Chapter 5: Sample Size Calculations with R: Level 1
- Chapter 6: Sample Size Calculations with R: Level 2
- Chapter 7: Binomial Regression in R
- Chapter 8: Computing Tolerance Intervals and Regions Using R
- Chapter 9: Modeling the Probability of Second Cancer in Controlled Clinical Trials
- Chapter 10: Bayesian Networks
- Subject Index