Mathematical Modeling
Process and Presentation
- 1st Edition - September 11, 2026
- Latest edition
- Authors: Amanda Beecher, Eric Marland, Kayla Blyman, Jessica Libertini
- Language: English
Mathematical Modeling: Process and Presentation offers a comprehensive introduction to the art of mathematical modeling, engaging students through thought-provoking questi… Read more
Description
Description
Mathematical Modeling: Process and Presentation offers a comprehensive introduction to the art of mathematical modeling, engaging students through thought-provoking questions and interactive content. Each chapter presents a different canonical modeling type, guiding readers through the essential components of the modeling process, from problem posing and assumptions to reflection and purpose definition. With relatable examples, such as estimating efforts in balloon filling or developing metrics for college roommate matching, students are encouraged to explore and expand on the models presented. This text stands out by revisiting the modeling process throughout, rather than focusing solely on examples, fostering a deeper understanding of the methodology. Accessible to a broad audience, it invites readers to apply their mathematical tools at varying levels of sophistication, ensuring that the focus remains on the core process, which remains relevant as their knowledge grows. Mathematical Modeling: Process and Presentation is an invaluable resource for undergraduate students and early graduate-level mathematics learners seeking to enhance their modeling skills and engage with real-world applications.
Key features
Key features
- Introduces mathematical modeling processes through engaging examples and thought-provoking questions
- Covers foundational topics such as problem posing, assumptions, and mathematical formulation, using relatable examples to illustrate each concept
- Addresses a critical gap in existing texts by focusing on the modeling process throughout, fostering deeper understanding
- Serves as an essential resource for junior and senior undergraduate students, as well as early graduate-level mathematics students seeking to enhance their modeling skills
- Includes chapter-end questions that reinforce the modeling process, encourage exploration of related topics, and connect concepts to broader mathematical ideas
Readership
Readership
Junior and Senior level undergraduate or early graduate level mathematics students
Table of contents
Table of contents
1. The Start of Modeling
2. Estimation and Effort
3. Diagrams and Graphs
4. Priority Matching
5. Probability and Odds
6. Strategy in the face of randomness
7. Dynamics and Control
8. Flow and Boundaries
9. Pool Modeling
10. Proportional Dynamics
11. Linear Programming
12. Stochastic Elements
13. Geometry and scaling
14. Pool Modeling revisited
15. Qualitative Modeling
16. Priority Ranking
17. Dissemination
2. Estimation and Effort
3. Diagrams and Graphs
4. Priority Matching
5. Probability and Odds
6. Strategy in the face of randomness
7. Dynamics and Control
8. Flow and Boundaries
9. Pool Modeling
10. Proportional Dynamics
11. Linear Programming
12. Stochastic Elements
13. Geometry and scaling
14. Pool Modeling revisited
15. Qualitative Modeling
16. Priority Ranking
17. Dissemination
Product details
Product details
- Edition: 1
- Latest edition
- Published: May 3, 2027
- Language: English
About the authors
About the authors
AB
Amanda Beecher
Amanda Beecher is Professor of Mathematics at Ramapo College of New Jersey. She completed her PhD at the State University of New York at Albany where her dissertation was in the field of commutative algebra. She has provided professional development workshops for K-12 educators in mathematical modeling and data science. She is the founding department head for the Data Science program at Ramapo College. For many years, Amanda has been both a triage judge and a final judge for COMAP's MCM and ICM contests in mathematical modeling. She has co-authored many of the contest problems and was Director of the COMAP ICM contest for 4 years.
Affiliations and expertise
Professor of Mathematics, Ramapo College of New Jersey, USAEM
Eric Marland
Eric Marland is Professor of Mathematics at Appalachian State University. He completed his PhD at the University of Utah where his dissertation involved modeling the dynamics of muscle contraction. He pursued post-doctoral studies at the Institute for Theoretical Dynamics at the University of California at Davis, studying models of cellular motility. His more recent research has covered many areas of mathematical modeling but has primary focused on forest dynamics and climate policy. He helped found the MAA's (Mathematical Association of America) special interest group SIGMAA) on Theoretical and Computational Biology and has led the SIGMAA on Environmental Mathematics. He has also run numerous professional development workshops on mathematical modeling, computational biology, humanistic mathematics, and communicating science. He has worked on various projects funded by the USFS, NSF, and NASA.
Affiliations and expertise
Professor of Mathematics, Appalachian State University, USAKB
Kayla Blyman
Kayla Blyman is Associate Professor of Mathematics at Saint Martin's University. She completed her PhD at the University of Kentucky where her dissertation was in the field of STEM Education. She currently serves as Department Chair for the Mathematics Department at Saint Martin's. For many years, Kayla has been both a triage judge and a final judge for COMAP's contest in mathematical modeling (MCM, ICM, HiMCM, and MidMCM). She currently serves as Director of both COMAP's ICM and MidMCM contests in mathematical modeling. She is on the editorial board for the UMAP journal as the Teaching Modeling Department Editor.
Affiliations and expertise
Associate Professor of Mathematics. Saint Martin's University, USA