A Primer in Biological Data Analysis and Visualization Using R
Hartvigsen, Gregg.
A Primer in Biological Data Analysis and Visualization Using R [electronic resource]. - New York : Columbia University Press, 2021. - 1 online resource (217 p.)
Description based upon print version of record.
Intro -- 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
This text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. This second edition has been revised to be current with the versions of R software released since the book's original publication. It features updated terminology, sources, and examples throughout.
0231554400 9780231554404
22573/ctv1q2rd22 JSTOR
R (Computer program language)
Mathematical statistics--Data processing.
SCIENCE / Life Sciences / Biology
Electronic books.
QA276.45.R3
005.13/3
A Primer in Biological Data Analysis and Visualization Using R [electronic resource]. - New York : Columbia University Press, 2021. - 1 online resource (217 p.)
Description based upon print version of record.
Intro -- 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
This text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. This second edition has been revised to be current with the versions of R software released since the book's original publication. It features updated terminology, sources, and examples throughout.
0231554400 9780231554404
22573/ctv1q2rd22 JSTOR
R (Computer program language)
Mathematical statistics--Data processing.
SCIENCE / Life Sciences / Biology
Electronic books.
QA276.45.R3
005.13/3