Author Description
Learning how to get answers from data is an integral part of modern training in the natural, physical, social, and engineering sciences. One of the most exciting changes in data management and analysis during the last decade has been the growth of open source software. The open source statistics and programming language R has emerged as a critical component of any researcher's toolbox. Indeed, R is rapidly becoming the standard software for analyses, graphical presentations, and programming in the biological sciences. This book provides a functional introduction for biologists new to R.
Menrva's Summary
THE THESIS
This book investigates the fundamental question of how biologists can effectively utilize the R programming language to manage, analyze, and visualize complex scientific data. Author Andrew P. Beckerman, an experienced researcher and educator, provides a structured framework designed to transition novices from basic data handling to more sophisticated statistical programming. By focusing on the specific needs of the biological sciences, the text bridges the gap between general programming concepts and practical research applications.
THE SCOPE MAP
What You Will Find
- Introduction to the R environment and interface
- Data manipulation and management techniques
- Methods for generating graphical data presentations
- Statistical analysis workflows tailored for biological research
- Practical coding exercises for scientific problem-solving
Scope Limits
- Advanced machine learning or complex bioinformatics algorithms
- Comprehensive coverage of all R packages beyond core functionality
- Theoretical statistics without direct application to biological datasets
THE AUTHORITY PERSPECTIVE
Experts frequently identify this text as a highly accessible entry point for researchers transitioning from traditional spreadsheet software to programmatic data analysis. Readers often note the clarity of the prose and the logical progression of the exercises, making it a standard resource for students and professionals in the biological sciences.
Page Count:
113
Publication Date:
2012-01-01
ISBN-10:
0191624144
ISBN-13:
9780191624148
Science
Statistics
BIOINFORMATICS
Reference
Programming
Computers - Languages Programming
Probability & Statistics
Health Sciences
Biology
Biology General
Data Analysis
Physical Sciences