A Primer in Biological Data Analysis and Visualization Using R

by Gregg Hartvigsen

Overview

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences.

Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.

Product Details

ISBN-13:	9780231166997
Publisher:	Columbia University Press
Publication date:	02/18/2014
Pages:	248
Product dimensions:	6.90(w) x 9.90(h) x 0.70(d)
Age Range:	18 Years

About the Author

Gregg Hartvigsen is a professor in the Department of Biology at the State University of New York at Geneseo. He taught a workshop on network analysis using R at the National Institute for Mathematical and Biological Synthesis at the University of Tennessee, Knoxville, and was a visiting scientist and site reviewer for the Mathematical Biosciences Institute at Ohio State University. He also served as co-PI on a National Science Foundation training grant for undergraduate biology and mathematics.

Table of Contents

Preface to the Second Edition
Acknowledgments
Introduction
1. Introducing Our Software Team
2. Getting Data Into R
3. Working with Your Data
4. Tell Me About My Data
5. Visualizing Your Data
6 An Overview of Science, Hypothesis Testing, Experimental Design, and Inference
7. Hypothesis Tests: Using One- and Two-Sample Tests
8. Hypothesis Tests: Differences Among Multiple Samples
9. Hypothesis Tests: Linear Relationships
10. Hypothesis Tests: Observed and Expected Values
11. A few More Advanced Procedures
12. An Introduction to Computer Programming
13. Final Thoughts
Appendix: Solutions to Select Problems
Bibliography
Index

Editorial Reviews

A well-written overview of both biostatistics and R programming.... this volume will fill an important niche for undergraduate biology.

Quarterly Review of Biology

Hartvigsen has succeeded in accomplishing his stated objectives. Buy the book and share the knowledge with students… the book is relevant, timely, and just what is needed with current trends in science education.

Ecology

"An excellent, easy to read introduction to biostatistics and the software program R. Simple but rigorous, with top notch coverage of R. I would recommend this book to colleagues and students."

Dr. Andy Conway

An excellent, easy-to-read introduction to biostatistics and the software program R. Simple but rigorous, with top-notch coverage of R. I would recommend this new edition to both colleagues and students.

Andrew Conway

An excellent, easy-to-read introduction to biostatistics and the software program R. Simple but rigorous, with top-notch coverage of R. I would recommend this book to both colleagues and students.

Andy Conway

A recommendation for any college-level course strong in biostatistics and modeling...a fine guide for science and R programming students alike.

Midwest Book Review

A Primer in Biological Data Analysis and Visualization Using R does a thorough job of introducing students to R and showing them how to perform basic statistical tests for normality, homogeneity, and other elements of data sets. Additionally, the book's focus on the application of statistical tests is most helpful for students in later coursework.

Cecilia Brothers