Cantitate/Preț
Produs

Data Science: Classroom Resource Materials

Editat de Jason Douma, Tim Chartier
en Limba Engleză Paperback – 11 noi 2026
Motivated by the rapid growth of interest in data science in recent years, many faculty are seeking ways to incorporate data-related concepts into their existing curricula. This book presents a collection of classroom-tested activities that enable instructors to integrate meaningful, data-rich experiences into their mathematics courses. Each module has been carefully designed for seamless incorporation into courses such as finite mathematics, calculus, and linear algebra. Through these activities, students encounter mathematical concepts in authentic, data-driven contexts. Many of the featured scenarios are inspired by real-world problems, such as determining optimal locations for concession stands in a theme park or analyzing the fairness of NFL overtime rules. Each chapter discusses the motivation and structure of the activity, the tools and techniques used to address the problem, and pedagogical considerations for implementation. In addition, every module includes guidance on locating or generating the relevant datasets. Quickstart boxes at the beginning of each chapter make it easy to identify the key ideas and essential components of each module at a glance. To maximize flexibility, student prerequisites have been intentionally kept to a minimum. Instructors are not required to have prior experience or training in data science.
Citește tot Restrânge

Din seria Classroom Resource Materials

Preț: 43826 lei

Precomandă

Puncte Express: 657

Carte nepublicată încă

Livrare prin curier în România Precomanda se expediază când titlul devine disponibil.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Doresc să fiu notificat când acest titlu va fi disponibil:

Specificații

ISBN-13: 9781470477950
ISBN-10: 1470477955
Pagini: 158
Dimensiuni: 178 x 254 mm
Editura: American Mathematical Society
Colecția Classroom Resource Materials
Seria Classroom Resource Materials


Notă biografică

Tim ChartierM, Davidson College, NC, and Jason Douma, University of Sioux Falls, SD

Cuprins

  • Elizabeth L. Bouzarth and Kevin R. Hutson, Introducing $k$-means clustering through a real-world theme park example
  • Nora Gilbertson, Jake Price, and Jeremy Upsal, Predicting movie preferences using the $k$-nearest neighbors algorithm
  • Boyan Kostadinov, From Kepler to code: Data science lessons inspired by physics
  • Russell E. Goodman, A geospatial data science lesson...inspired by a comedian!
  • Nicholas Gorgievski and Megan Powell, Analyzing first-possession advantage in NFL overtime using Markov chains
  • Haiyan Su, Data-driven problem-solving through partnerships with business and industry in a mathematics topic course
  • Mutiara Sonjaja, Numbers to knowledge: A hands-on modeling module for quantitative reasoning
  • R. N. Uma, Adrienne A. Smith, Rebecca A. Zulli Lowe, and Alade O. Tokuta, Data science for social justice
  • Daniel T. Kaplan, Linear algebra in introductory calculus
  • Bibliography
  • Index