Practical R for Biologists: An Introduction

R is a free, open-source statistical programming environment used by scientists, engineers, economists, market researchers, and medical professionals. This book covers biology students' data analysis needs, from first-year undergraduates to post-graduate levels. Chapters are organized around topics such as graphing, classical statistical tests, statistical modeling, mapping, and text parsing. Examples are based on real scientific studies and cover the use of more R functions than necessary to get a p-value or plot. The authors have extensive teaching experience and make the passage into R programming gentle and easy while guiding the reader to tackle complicated programming.

Format: Paperback / softback
Length: 424 pages
Publication date: 15 January 2021
Publisher: CABI Publishing

R is a powerful and freely available statistical programming environment that offers a wide range of statistical analysis tools and graphics outputs. It has gained widespread popularity among biologists, as well as scientists, engineers, economists, market researchers, and medical professionals. With a growing community of expert R users, new associated packages are constantly being developed, expanding the range of functionalities available. This text serves as a comprehensive guide for biology students, covering a wide range of R operations necessary for data analysis. It is designed to cater to students from first-year undergraduates to those embarking on post-graduate studies.

The chapters are organized around key topics such as graphing, classical statistical tests, statistical modeling, mapping, and text parsing. Each example is based on real scientific studies, demonstrating the use of more R functions than what is typically required for basic p-value calculations or plot generation. The book progresses from simple plots to more complex analyses and programming, providing a step-by-step approach to data analysis.

The authors, with extensive teaching experience, have designed the text to make the transition into R programming as gentle and easy as possible. They provide clear explanations and examples, guiding students through the process while tackling more complicated programming concepts. The book also includes tips and best practices to enhance the learning experience and prepare students for a successful scientific career using R.

In conclusion, R is a versatile and powerful tool for statistical analysis, and this text provides an excellent introduction to its usage for biology students. With its comprehensive coverage, real-world examples, and gentle teaching approach, it equips students with the skills they need to analyze their own data and pursue scientific research using R. Whether you are a beginner or an experienced R user, this book is a valuable resource for advancing your statistical knowledge and achieving your research goals.

Weight: 1038g
Dimension: 243 x 173 x 32 (mm)
ISBN-13: 9781789245349