Mathematical Modeling in Biology
eBook - ePub

Mathematical Modeling in Biology

A Research Methods Approach

  1. 296 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Mathematical Modeling in Biology

A Research Methods Approach

Book details
Table of contents
Citations

About This Book

Mathematical Modeling in Biology: A Research Methods Approach is a textbook written primarily for advanced mathematics and science undergraduate students and graduate-level biology students. Although the applications center on ecology, the expertise of the authors, the methodology can be imported to any other science, including social science and economics. The aim of the book, beyond being a useful aid to teaching and learning the core modeling skills needed for mathematical biology, is to encourage students to think deeply and clearly about the meaning of mathematics in science and to learn significant research methods. Most importantly, it is hoped that students will experience some of the excitement of doing research.

Features

  • Minimal pre-requisites beyond a solid background in calculus, such as a calculus I course.
  • Suitable for upper division mathematics and sciences students and graduate-level biology students.
  • Provides sample MATLAB codes and instruction in Appendices along with datasets available on https://bit.ly/3fcLF3D

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Yes, you can access Mathematical Modeling in Biology by Shandelle M. Henson, James L. Hayward in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Chemistry. We have over one million books available in our catalogue for you to explore.

Information

Year
2022
ISBN
9781000806106
Edition
1

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Table of Contents
  8. Acknowledgments
  9. For Professors and Students
  10. Authors
  11. Section I Introduction to Modeling
  12. Section II Discrete-Time Models
  13. Section III Continuous-Time Models
  14. Section IV Regression Models
  15. Section V Appendix
  16. Index