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A Primer in Biological Data Analysis and Visualization Using R [electronic resource].

By: Material type: TextTextPublication details: New York : Columbia University Press, 2021.Description: 1 online resource (217 p.)ISBN:
  • 0231554400
  • 9780231554404
Subject(s): Genre/Form: Additional physical formats: Print version:: A Primer in Biological Data Analysis and Visualization Using RDDC classification:
  • 005.13/3 23
LOC classification:
  • QA276.45.R3
Online resources:
Contents:
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
Summary: 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.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Science Available
Total holds: 0

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.

Master record variable field(s) change: 072

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