With an emphasis on techniques, this volume focuses on the applications of basic mathematics and differential and integral calculus in the field of business, economics and the life and social sciences. All mathematical theorems, proofs and concepts are described intuitively and then mathematically. Reorganized and rewritten material includes chapters on exponentials and logarithms, curve sketching and optimization, application sections of straight lines and quadratic inequalities. A new section on difference equations and expanded coverage of differential equations is included.
MATEMAX is a bilingual schoolbook of mathematical problems written with the premise that one of the fundamental ways of learning mathematics, in addition to being one of the goals of the subject, is to solve problems. The book is designed for children and young teens and aims to teach mathematics in an entertaining way. Problems are based on familiar everyday situations, and helpful hints guide students to develop strategies before diving into calculations, leading to practice in abstract thinking, an essential feature of mathematics. Presented in both English and Spanish it also provides equal access to students, parents and teachers with facility in either or both languages. An online supplement is available upon request at [email protected]. This companion book provides complete solutions, alternative methods and additional suggestions to complement the short answers contained in the book. In addition, while problems are arranged in the book as they appear naturally in life, the companion text connects the mathematical tools with standard curricula. Here is a sampling of those pages. MATEMAX es un libro escolar bilingüe de problemas matemáticos escrito bajo la premisa de que una de las formas fundamentales de aprender matemática, además de ser uno de los objetivos de la asignatura, es resolver problemas. El libro está diseñado para niños y adolescentes y tiene como objetivo enseñar matemática de una manera entretenida. Los problemas se basan en situaciones cotidianas familiares, y sugerencias útiles guían a los estudiantes para desarrollar estrategias antes de sumergirse en los cálculos, lo que lleva a la práctica del pensamiento abstracto, una característica esencial de la matemática. Presentado tanto en inglés como en español, también proporciona un acceso igual a estudiantes, padres y maestros con facilidad en uno o ambos idiomas. Un suplemento en línea está disponible a pedido en [email protected]. Este libro acompañante proporciona soluciones completas, métodos alternativos y sugerencias adicionales para complementar las respuestas cortas contenidas en el libro. Además, mientras que los problemas están ubicados en el libro como aparecen naturalmente en la vida, el texto complementario conecta las herramientas matemáticas con los planes de estudio estándar. Aquí hay una muestra de esas páginas.
The digital revolution that we have experienced since the last quarter of the twentieth century has had some influence, yet to be analysed and extended, on the way mathematics is made, taught and learned. While the rate of innovation in these technologies is growing exponentially, the potential impact of most information technologies on mathematical education remains to be fully exploited. In particular, several authoritative voices point out that the technology that will most likely transform education in the coming years is artificial intelligence (AI). Interestingly, today AI is mainly associated with technologies to automate tasks and lower costs, thus serving primarily the interests of the political-administrative, industrial and commercial world. In this scenario, the world of education and, more specifically, didactics, appears at best as a mere user of AI techniques developed in other fields, forgetting that AI should play a much more relevant role here, serving the human being who is doing his work as a mathematician or who is learning mathematics. The AI4ME symposium at the International Centre for Mathematical Meetings (CIEM) in Castro Urdiales is a space for research and reflection to better understand the interconnected challenges of instrumental learning of mathematics and instrumental mathematics, taking advantage of the achievements and opportunities of Artificial Intelligence for Mathematical Education. This book of abstracts gathers the summaries of the talks presented at the symposium, as well as the conclusions of each of the four thematic groups.
Unique in its clarity, examples and range, Physical Mathematics explains as simply as possible the mathematics that graduate students and professional physicists need in their courses and research. The author illustrates the mathematics with numerous physical examples drawn from contemporary research. In addition to basic subjects such as linear algebra, Fourier analysis, complex variables, differential equations and Bessel functions, this textbook covers topics such as the singular-value decomposition, Lie algebras, the tensors and forms of general relativity, the central limit theorem and Kolmogorov test of statistics, the Monte Carlo methods of experimental and theoretical physics, the renormalization group of condensed-matter physics and the functional derivatives and Feynman path integrals of quantum field theory.
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.
