Computational Discovery on Jupyter

Neil J. Calkin, Eunice Y. S. Chan, Robert M. Corless

ISBN 10: 1611977495 / ISBN 13: 9781611977493

Published by Society for Industrial and Applied Mathematics,U.S., US, 2024

About this Item

This book uses Python to teach mathematics not found in the standard curriculum, so students learn a popular programming language as well as some interesting mathematics. Videos, images, programs, programming activities, pencil-and-paper activities, and associated Jupyter Notebooks accompany the text, and readers are encouraged to interact with and extend the material as well as contribute their own notebooks. Indeed, some of the material was created/discovered/invented/published first by the authors' students.Useful pedagogical features include using an active learning approach with topics not typically found in a standard math curriculum; introducing concepts using programming, not proof, with the goal of preparing readers for the need for proof; and accompanying all activities with a full discussion.Computational Discovery on Jupyter is for upper-level high school and lower-level college students. Graduate students in mathematics will also find it of interest.

Seller Inventory # LU-9781611977493

Bibliographic Details

• Title: Computational Discovery on Jupyter
• Publisher: Society for Industrial and Applied Mathematics,U.S., US
• Publication Date: 2024
• Language: English
• ISBN 10: 1611977495
• ISBN 13: 9781611977493
• Binding: Paperback
• Condition: New
• Weight: 272 grams

About this title

Synopsis

This book uses Python to teach mathematics not found in the standard curriculum, so students learn a popular programming language as well as some interesting mathematics. Videos, images, programs, programming activities, pencil-and-paper activities, and associated Jupyter Notebooks accompany the text, and readers are encouraged to interact with and extend the material as well as contribute their own notebooks. Indeed, some of the material was created/discovered/invented/published first by the authors' students.

Useful pedagogical features include using an active learning approach with topics not typically found in a standard math curriculum; introducing concepts using programming, not proof, with the goal of preparing readers for the need for proof; and accompanying all activities with a full discussion.

Computational Discovery on Jupyter is for upper-level high school and lower-level college students. Graduate students in mathematics will also find it of interest.

About the Author

Neil J. Calkin is a professor in the School of Mathematical and Statistical Sciences at Clemson University. He cofounded the Electronic Journal of Combinatorics with Herbert S. Wilf in 1994.

Eunice Y. S. Chan is an assistant professor in the School of Medicine at The Chinese University of Hong Kong Shenzhen, China. She was a postdoctoral fellow at the Centre for Medical Evidence, Decision Integrity and Clinical Impact (MEDICI Centre), Department of Anesthesia and Perioperative Medicine, Schulich School of Medicine and Dentistry at Western University in London, Ontario.

Robert M. Corless is Emeritus Distinguished University Professor at Western University, a member of the Rotman Institute of Philosophy, former scientific director of The Ontario Research Center for Computer Algebra, and an adjunct professor at the Cheriton School of Computer Science, the University of Waterloo. He is the editor-in-chief of Maple Transactions.