Libros de Matemáticas, página 40 de 472

Ahora en un solo libro usted puede estudiar las cuatro disciplinas básicas de la matemática: álgebra, trigonometría, geometría analítica y cálculo. Áreas en las que este libro ofrece una correlación lógica y equilibrio entre lo formal y lo intuitivo. Cada unidad muestra una lista de objetivos específicos de aprendizaje para que el estudiante conozca los requisitos mínimos que debe saber. Por su contenido y enfoque resulta de gran utilidad para estudiantes de bachillerato y de nivel medio superior, así como para cualquier persona que desee obtener conocimientos sobre los fundamentos básicos de la matemática. En esta séptima edición se han reestructurado los capítulos dedicados al "álgebra" y "funciones en los reales" además se añadió un capítulo dirigido al estudio del cálculo. Esta nueva edición cuenta con un mayor número de ejercicios y ejemplos.

Explanatory Model Analysis Explore Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment Today the true bottleneck in predictive modelling is neither the lack of data nor the lack of computational power nor inadequate algorithms nor the lack of flexible models It is the lack of tools for model exploration extraction of relationships learned by the model model explanation understanding the key factors influencing model decisions and model examination identification of model weaknesses and evaluation of model s performance This book presents a collection of model agnostic methods that may be used for any black box model together with real world applications to classification and regression problems

Concentration inequalities for functions of independent random variables is an area of probability theory that has witnessed a great revolution in the last few decades, and has applications in a wide variety of areas such as machine learning, statistics, discrete mathematics, and high-dimensional geometry. Roughly speaking, if a function of many independent random variables does not depend too much on any of the variables then it is concentrated in the sense that with high probability, it is close to its expected value. This book offers a host of inequalities to illustrate this rich theory in an accessible way by covering the key developments and applications in the field. The authors describe the interplay between the probabilistic structure (independence) and a variety of tools ranging from functional inequalities to transportation arguments to information theory. Applications to the study of empirical processes, random projections, random matrix theory, and threshold phenomena are also presented.A self-contained introduction to concentration inequalities, it includes a survey of concentration of sums of independent random variables, variance bounds, the entropy method, and the transportation method. Deep connections with isoperimetric problems are revealed whilst special attention is paid to applications to the supremum of empirical processes. Written by leading experts in the field and containing extensive exercise sections this book will be an invaluable resource for researchers and graduate students in mathematics, theoretical computer science, and engineering.

Noted for its crystal clear explanations, this book is considered the most comprehensive introductory text to structural equation modeling (SEM). Noted for its thorough review of basic concepts and a wide variety of models, this book better prepares readers to apply SEM to a variety of research questions. Programming details and the use of algebra are kept to a minimum to help readers easily grasp the concepts so they can conduct their own analysis and critique related research. Featuring a greater emphasis on statistical power and model validation than other texts, each chapter features key concepts, examples from various disciplines, tables and figures, a summary, and exercises. Highlights of the extensively revised 4th edition include:-Uses different SEM software (not just Lisrel) including Amos, EQS, LISREL, Mplus, and R to demonstrate applications.-Detailed introduction to the statistical methods related to SEM including correlation, regression, and factor analysis to maximize understanding (Chs. 1 - 6).-The 5 step approach to modeling data (specification, identification, estimation, testing, and modification) is now covered in more detail and prior to the modeling chapters to provide a more coherent view of how to create models and interpret results (ch. 7).-More discussion of hypothesis testing, power, sampling, effect sizes, and model fit, critical topics for beginning modelers (ch. 7).- Each model chapter now focuses on one technique to enhance understanding by providing more description, assumptions, and interpretation of results, and an exercise related to analysis and output (Chs. 8 -15).-The use of SPSS AMOS diagrams to describe the theoretical models.-The key features of each of the software packages (Ch. 1).-Guidelines for reporting SEM research (Ch. 16).

El libro desarrolla los contenidos clásicos del Análisis Matemático: Variable Compleja, Ecuaciones Diferenciales Ordinarias y Métodos Numéricos para las ecuaciones diferenciales.Está dirigido a estudiantes de ingenieria. Con contenidos seleccionados teniendo en cuenta las aplicaciones que se dan en las correspondientes asignaturas.Se mantiene un orden coherente en la presentacion y desarrollo de los distintos conceptos que se van introduciendo, incorporando al final de cada apartado ejemplos totalmente resueltos que contribuyen a la comprension y asimilacion teorica. Al final de cada capitulo se incluyen ejercicios y problemas que en algunos casos se han añadido sus soluciones.Es el unico texto editado en español que recoge todos los aspectos citados anteriormente de forma que el profesorado pueda utilizarlo como guia y recomendarlo a sus alumnos.

Covers the main theorems of algebraic number theory, including function fields over finite constant fields.

This book, about the nature and techniques of mathematical modeling, is oriented towards simple efficient implementations on computers. The text is in three sections. The first covers exact and approximate analytical techniques; the second, numerical methods; the third, model inference based on observations; and the last, the special role of time in modeling. Each of the topics in the book would be the worthy subject of a dedicated text, but only by presenting the material in this way is it possible to make so much material accessible to so many people. Each chapter presents a concise summary of the core results in an area, providing an orientation to what they can (and cannot) do, enough background to use them to solve typical problems, and pointers to access the literature for particular applications. The text is complemented by extensive worked problems.

This is the third edition of the highly successful introduction to the use of generating functions and series in combinatorial mathematics. This new edition provides a clear, unified introduction to the basic enumerative applications of generating functions.Special features:- Provides applications to the cycle index of the symmetric group, permutations and square roots, counting polyominoes, and exact covering sequences- Features an appendix on using Mapie and Mathematica to work with generating functions- Includes new exercises with complete solutions at the end of each chapter

This bundle includes Liljedahls bestselling anchor book Building Thinking Classrooms in Mathematics, Grades K-12 and his new supplement title Modifying Your Thinking Classroom for Different Settings. Much of what happens in math classrooms today is guided by institutional norms laid down at the inception of an industrial-age model of public education. These norms have enabled a culture of teaching and learning that is often devoid of student thinking. Building Thinking Classrooms presents the results of over 15 years of research into which teaching practices are effective for getting students to think and which ones do not. This book takes you through a step-by-step approach that you can use to transform your classroom from a space where students mimic to a space where students think. But how do these practices work in a classroom with social distancing or in settings that are not always face-to-face? The follow-up supplement, Modifying Your Thinking Classroom for Different Settings, will answer those questions, and more. It walks teachers through how to adapt the 14 practices for 12 distinct settings, some of which came about as a result of the COVID-19 pandemic.