Автор: Sufyan bin Uzayr
Издательство: CRC Press
Год: 2024
Страниц: 297
Язык: английский
Формат: pdf (true)
Размер: 11.3 MB
R is a statistical computing and graphics programming language that you can use to clean, analyze, and graph data. It is widely used by researchers from various disciplines to estimate and display results and by teachers of statistics and research methods. This book is a detailed guide for beginners to understand R with an explanation of core statistical and research ideas.
One of the powerful characteristics of R is that it is open-source, which means that anyone can access the underlying code used to run the program and add their own code for free. It will always be able to perform the latest statistical analyses as soon as anyone thinks of them. R corrects mistakes quickly and transparently and has put together a community of programming and statistical experts that you can turn to for help.
Mastering R: A Beginner’s Guide not only explains how to program but also how to use R for visualization and modeling. The fundamental principles of R explained here are helpful to beginner and intermediate users interested in learning this highly technological and diverse language.
Data Science continues to emerge as one of the most promising and indemand career paths for qualified professionals. Today, data professionals understand that they must overcome the traditional skills of Big Data analysis, data mining, and programming. In order to uncover useful insights for their organizations, data scientists must master the full spectrum of the data science lifecycle and have a level of flexibility and understanding to maximize return at each stage of the process. Data Science is an exciting discipline that allows you to transform raw data into understanding and knowledge.
R is an integrated set of facilities software for data manipulation, computation, and graphical display. It includes efficient equipment for handling and storing data, a set of operators for calculations on arrays, especially matrices, a large, coherent, integrated collection of intermediary tools for data analysis, graphic devices for data analysis and display on screen or in printed form a well-developed, simple and efficient programming language that includes conditionals, loops, user-defined recursive functions, and input and output devices. The term “environment” is intended to characterize it as a planned and coherent system, rather than an increment accretion of very specific and inflexible tools, as is often the case with other data analysis software.
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