
This textbook is rich with real-life data sets, uses RStudio to streamline computations, builds "big picture" conceptual understandings, and applies them in diverse settings. Mathematical Modeling and Applied Calculus will develop the insights and skills needed to describe and model many different aspects of our world. This textbook provides an excellent introduction to the process of mathematical modeling, the method of least squares, and both differential and integral calculus, perfectly meeting the needs of today's students. Mathematical Modeling and Applied Calculus provides a modern outline of the ideas of Calculus and is aimed at those who do not intend to enter the traditional calculus sequence. Topics that are not traditionally taught in a one-semester Calculus course, such as dimensional analysis and the method of least squares, are woven together with the ideas of mathematical modeling and the ideas of calculus to provide a rich experience and a large toolbox of mathematical techniques for future studies. Additionally, multivariable functions are interspersed throughout the text, presented alongside their single-variable counterparts. This text provides a fresh take on these ideas that is ideal for the modern student.
This text investigates how mathematical modeling and calculus can be integrated to provide a functional, real-world analytical framework for students outside the traditional calculus sequence. Authors Alex McAllister and Joel Kilty, both experienced mathematics educators, utilize a data-driven approach to bridge the gap between abstract theory and practical application. By emphasizing conceptual understanding over rote memorization, the authors argue that students can develop a versatile mathematical toolbox applicable to diverse professional and academic fields.
What You Will Find
Scope Limits
Educators frequently note that this text serves as a modern alternative for students seeking applied skills rather than theoretical depth. Experts highlight the inclusion of RStudio and real-world data sets as a significant advantage for students preparing for data-centric careers.
Page Count:
816
Publication Date:
2018-01-01
Publisher:
OUP Oxford
ISBN-10:
0192558137
ISBN-13:
9780192558138
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