Название: Introduction to Statistics Using R Автор: Mustapha Akinkunmi
Издательство: Morgan & Claypool Publishers
Год: 2019
Страниц: 237
Язык: английский
Формат: pdf (true)
Размер: 22.3 MB
Introduction to Statistics Using R is organized into 13 major chapters. Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-life practical examples in this book and each of the examples is written in R codes to acquaint the readers with some statistical methods while simultaneously learning R scripts.
R is a programming language designed for statistical analysis and graphics. It is based on S-plus which was developed by Ross Ihaka and Robert Gentleman from the University of Auckland, New Zealand, and R can be used to open multiple datasets. R is an open-source software which can be downloaded from the official site. Other statistical packages are SPSS, SAS, and Stata but they are not open source. Apart from this, there are large R group users online that can provide real-time answers to questions, and that also contribute to add packages to R. Packages increase the functions that are available for use, thus expanding the users' abilities. The R Development Core Team is responsible for maintaining the source code of R.
Why turn to R?
R software provides the following advantages:
1. R is free (meaning open-source software).
2. Any type of data analysis can be executed in R.
3. R includes advanced statistical procedures not yet present in other packages.
4. The most comprehensive and powerful feature for visualizing complex data is available in R.
5. Importing data from a wide variety of sources can be easily done with R.
6. R is able to access data directly from web pages, social media sites, and a wide range of online data services.
7. R software generates an easy and straightforward platform for programming new statistical techniques.
8. It is simple to integrate applications written in other programming languages (such as C++, Java, Python, PHP, Pentaho, SAS, and SPSS) into R.
9. R can operate on any operating system such as Windows, Unix, and Mac OSX. It can also be installed on an iPhone. It is also possible to use R on an Android phone.
10. R offers a variety of graphic user interfaces (GUIs) if you are not interested in learning a new language.
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