Software for Data Analysis: Programming with R. Statistics and Computing.

by John M. Chambers

Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in the face of the data flood that often faces statisticians. It is important to recognize the appropriate design, and to understand how to effectively implement it, being aware that the default settings from a computer package can easily provide an incorrect analysis. The goal of this book is to describe the principles that drive good design, paying attention to both the theoretical background and the problems arising from real experimental situations. Designs are motivated through actual experiments, ranging from the timeless agricultural randomized complete block, to microarray experiments, which naturally lead to split plot designs and balanced incomplete blocks.

Genres: Nonfiction, Computers, Textbooks, Science, Reference, Artificial Intelligence

513 pages, ebook

First published January 1, 2008

Reviews

[Charles Godfrey Kamukama]

John M. Chambers skillfully presents R programming in a practical and accessible manner, making it approachable not only for novice non-programmers but also for statisticians. With his step-by-step approach, readers can easily grasp the fundamentals of R analysis and programming, enabling them to analyze data with confidence and ease.

For statisticians and data analysts, overlooking this valuable book would be a missed opportunity to stay relevant in the constantly evolving landscape of data analysis. Embracing R programming and the latest data analysis techniques is crucial for professionals seeking to thrive in the ever-changing computer era. By delving into the wealth of knowledge offered by this book, they can equip themselves with the skills necessary to adapt and excel in this new and incomparable trend in data analysis and programming.

[Amit · Rating 3 out of 5]

Lots of information but rather poorly organized. Writing style is verbose and takes some effort.