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"R (Computer program language)"
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R quick syntax reference : a pocket guide to the language, APIs and library
\"This handy reference book detailing the intricacies of R updates the popular first edition by adding R version 3.4 and 3.5 features. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings, and an example using the Twitter API. With a copy of the \"R quick syntax reference\" in hand, you will find that you are able to use the multitude of functions available in R and are even able to write your own functions to explore and analyze data.\"-- Provided by publisher
Book
Mastering SAP ABAP
ABAP is an established and complex programming language in the IT industry. This book will give you confidence in using the latest ABAP programming techniques and applying legacy constructions with the help of practical examples.
eBook
Data mining and business analytics with R
Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification.
Highlighting both underlying concepts and practical computational skills, Data Mining and Business Analytics with R begins with coverage of standard linear regression and the importance of parsimony in statistical modeling. The book includes important topics such as penalty-based variable selection (LASSO); logistic regression; regression and classification trees; clustering; principal components and partial least squares; and the analysis of text and network data. In addition, the book presents:
* A thorough discussion and extensive demonstration of the theory behind the most useful data mining tools
* Illustrations of how to use the outlined concepts in real-world situations
* Readily available additional data sets and related R code allowing readers to apply their own analyses to the discussed materials
* Numerous exercises to help readers with computing skills and deepen their understanding of the material
Data Mining and Business Analytics with R is an excellent graduate-level textbook for courses on data mining and business analytics. The book is also a valuable reference for practitioners who collect and analyze data in the fields of finance, operations management, marketing, and the information sciences.
eBook
Propagating Terraces and the Dynamics of Front-Like Solutions of Reaction-Diffusion Equations on ℝ
We consider semilinear parabolic equations of the form
eBook
The essential R reference
An essential library of basic commands you can copy and paste into R The powerful and open-source statistical programming language R is rapidly growing in popularity, but it requires that you type in commands at the keyboard rather than use a mouse, so you have to learn the language of R. But there is a shortcut, and that's where this unique book comes in. A companion book to Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, this practical reference is a library of basic R commands that you can copy and paste into R to perform many types of statistical analyses. Whether you're in technology, science, medicine, business, or engineering, you can quickly turn to your topic in this handy book and find the commands you need. Comprehensive command reference for the R programming language and a companion book to Visualize This: The FlowingData Guide to Design, Visualization, and Statistics Combines elements of a dictionary, glossary, and thesaurus for the R language Provides easy accessibility to the commands you need, by topic, which you can cut and paste into R as needed Covers getting, saving, examining, and manipulating data; statistical test and math; and all the things you can do with graphs Also includes a collection of utilities that you'll find useful Simplify the complex statistical R programming language with The Essential R Reference. .
eBook
SAS for R users : a book for budding data scientists
\"This book will enable students and practitioners to easily switch from R to SAS and vice versa. R has better statistical and graphical tools, while SAS has faster data handling, is easier to learn and is the leading corporate software in analytics. This book builds a cross-functional framework for students who already know R but may need to work on SAS language in corporate environments. Using a simple how-to-do-it in a step-by-step way approach, the book presents an analytics workflow similar to those used by the everyday data scientist. The book is designed to be compatible with the latest R packages as well as SAS University Edition. It also includes advanced section for the reader who wishes to get a greater understanding of more advanced methods. The book will be useful to students, researchers, and practitioners globally as well as anyone looking to get a job in data science today\"-- Provided by publisher.
Book
Statistical hypothesis testing with SAS and R
A comprehensive guide to statistical hypothesis testing with examples in SAS and R
When analyzing datasets the following questions often arise:
Is there a short hand procedure for a statistical test available in SAS or R?
If so, how do I use it?
If not, how do I program the test myself?
This book answers these questions and provides an overview of the most common
statistical test problems in a comprehensive way, making it easy to find and perform
an appropriate statistical test.
A general summary of statistical test theory is presented, along with a basic
description for each test, including the necessary prerequisites, assumptions, the
formal test problem and the test statistic. Examples in both SAS and R are provided,
along with program code to perform the test, resulting output and remarks
explaining the necessary program parameters.
Key features:
• Provides examples in both SAS and R for each test presented.
• Looks at the most common statistical tests, displayed in a clear and easy to follow way.
• Supported by a supplementary website http://www.d-taeger.de [http://www.d-taeger.de/] featuring example
program code.
Academics, practitioners and SAS and R programmers will find this book a valuable
resource. Students using SAS and R will also find it an excellent choice for reference
and data analysis.
eBook