Download or read book College Algebra written by Jay Abramson and published by . This book was released on 2018-01-07 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt: College Algebra provides a comprehensive exploration of algebraic principles and meets scope and sequence requirements for a typical introductory algebra course. The modular approach and richness of content ensure that the book meets the needs of a variety of courses. College Algebra offers a wealth of examples with detailed, conceptual explanations, building a strong foundation in the material before asking students to apply what they've learned. Coverage and Scope In determining the concepts, skills, and topics to cover, we engaged dozens of highly experienced instructors with a range of student audiences. The resulting scope and sequence proceeds logically while allowing for a significant amount of flexibility in instruction. Chapters 1 and 2 provide both a review and foundation for study of Functions that begins in Chapter 3. The authors recognize that while some institutions may find this material a prerequisite, other institutions have told us that they have a cohort that need the prerequisite skills built into the course. Chapter 1: Prerequisites Chapter 2: Equations and Inequalities Chapters 3-6: The Algebraic Functions Chapter 3: Functions Chapter 4: Linear Functions Chapter 5: Polynomial and Rational Functions Chapter 6: Exponential and Logarithm Functions Chapters 7-9: Further Study in College Algebra Chapter 7: Systems of Equations and Inequalities Chapter 8: Analytic Geometry Chapter 9: Sequences, Probability and Counting Theory

Download or read book Mathematical Modeling written by Sandip Banerjee and published by CRC Press. This book was released on 2021-11-11 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling: Models, Analysis and Applications, Second Edition introduces models of both discrete and continuous systems. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject. Beginning with the step-by-step guidance of model formulation, this book equips the reader about modeling with difference equations (discrete models), ODE’s, PDE’s, delay and stochastic differential equations (continuous models). This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. A unique feature of the book is the breadth of coverage of different examples on mathematical modelling, which include population models, economic models, arms race models, combat models, learning model, alcohol dynamics model, carbon dating, drug distribution models, mechanical oscillation models, epidemic models, tumor models, traffic flow models, crime flow models, spatial models, football team performance model, breathing model, two neuron system model, zombie model and model on love affairs. Common themes such as equilibrium points, stability, phase plane analysis, bifurcations, limit cycles, period doubling and chaos run through several chapters and their interpretations in the context of the model have been highlighted. In chapter 3, a section on estimation of system parameters with real life data for model validation has also been discussed. Features Covers discrete, continuous, spatial, delayed and stochastic models. Over 250 illustrations, 300 examples and exercises with complete solutions. Incorporates MATHEMATICA® and MATLAB®, each chapter contains Mathematica and Matlab codes used to display numerical results (available at CRC website). Separate sections for Projects. Several exercise problems can also be used for projects. Presents real life examples of discrete and continuous scenarios. The book is ideal for an introductory course for undergraduate and graduate students, engineers, applied mathematicians and researchers working in various areas of natural and applied sciences.

Download or read book Mathematical Models with Applications written by Daniel L. Timmons and published by Brooks/Cole Publishing Company. This book was released on 2006-03 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text makes math fun, approachable, and applicable in everyday life. The authors provide algebraic modeling concepts and solutions in non-threatening, easy-to-understand language with numerous step-by-step examples to illustrate ideas. Whether they are going on to study early childhood education, graphic arts, automotive technologies, criminal justice, or something else, students will discover that the practical applications of mathematical modeling will continue to be useful well after they have finished this course.

Download or read book Object Models written by Peter Coad and published by Pearson Education. This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a new edition of this pack which covers the three leading object modelling notations, Coad, OMT and the new Unified (Booch-Rumbaugh) methodology. It presents 177 state-of-the-art strategies and 31 patterns for object model development. The new edition includes 29 new strategies which include: using feature milestones to deliver results more quickly; extracting useful content from data models; using patterns to discover new features, separating definition from usage; when to use, or not use, inheritance; how to decide whether you need an attribute or something more; and why you should nearly always ask for more than a data value.

Download or read book Linear and Generalized Linear Mixed Models and Their Applications written by Jiming Jiang and published by Springer Science & Business Media. This book was released on 2007-05-30 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis.

Download or read book Dynamic Programming written by Eric V. Denardo and published by Courier Corporation. This book was released on 2012-12-27 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed both for those who seek an acquaintance with dynamic programming and for those wishing to become experts, this text is accessible to anyone who's taken a course in operations research. It starts with a basic introduction to sequential decision processes and proceeds to the use of dynamic programming in studying models of resource allocation. Subsequent topics include methods for approximating solutions of control problems in continuous time, production control, decision-making in the face of an uncertain future, and inventory control models. The final chapter introduces sequential decision processes that lack fixed planning horizons, and the supplementary chapters treat data structures and the basic properties of convex functions. 1982 edition. Preface to the Dover Edition.

Download or read book Mathematical Models and Applications written by Daniel P. Maki and published by Prentice Hall. This book was released on 1973 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book began as lecture notes developed in connection with a course of the same name given since 1968 at Indiana University. The audience can be loosely grouped as follows: junior and senior mathematics majors, many of whom contemplate graduate work in other fields; undergraduate and graduate students majoring in the social and life sciences and in business; and prospective secondary teachers of mathematics. In addition, portions of the material have been used in NSF institutes for mathematics teachers. The goal of the course has been to provide the student with an appreciation for, an understanding of, and a facility in the use of mathematics in other fields. The role of mathematical models in explaining and predicting phenomena arising in the real world is the central theme." --Preface.

Download or read book Agent Based Models written by Nigel Gilbert and published by SAGE. This book was released on 2008 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aimed at readers with minimal experience in computer programming, this brief book provides a theoretical and methodological rationale for using ABM in the social sciences. It goes on to describe some carefully chosen examples from different disciplines, illustrating different approaches to ABM. It concludes with practical advice about how to design and create ABM, a discussion of validation procedures, and some guidelines about publishing articles based on ABM.

Download or read book Mathematical Models with Applications written by COMAP and published by Macmillan. This book was released on 2001-06-15 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: An innovative course that offers students an exciting new perspective on mathematics, Mathematical Models with Applications explores the same types of problems that math professionals encounter daily. The modeling process--forming a theory, testing it, and revisiting it based on the results of the test--is critical for learning how to think mathematically. Demonstrating this ability can open up a wide range of educational and professional opportunities for students. Mathematical Models with Applications has been designed for students who have completed Algebra I or Geometry and see this as the final course in their high school mathematics sequence, or who would like additional math preparation before Algebra II. Mathematical Models with Applications ListServ As a service to instructors using Mathematical Models with Applications, a listserv has been designed as a forum to share ideas, ask questions and learn new ways to enhance the learning experience for their students.

Download or read book Generalized Linear Models written by Raymond H. Myers and published by John Wiley & Sons. This book was released on 2012-01-20 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." —Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences. This new edition maintains its accessible approach to the topic by reviewing the various types of problems that support the use of GLMs and providing an overview of the basic, related concepts such as multiple linear regression, nonlinear regression, least squares, and the maximum likelihood estimation procedure. Incorporating the latest developments, new features of this Second Edition include: A new chapter on random effects and designs for GLMs A thoroughly revised chapter on logistic and Poisson regression, now with additional results on goodness of fit testing, nominal and ordinal responses, and overdispersion A new emphasis on GLM design, with added sections on designs for regression models and optimal designs for nonlinear regression models Expanded discussion of weighted least squares, including examples that illustrate how to estimate the weights Illustrations of R code to perform GLM analysis The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology and biopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS®, Minitab®, JMP®, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets. Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also serves as a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work.

Download or read book Handbook of Finite State Based Models and Applications written by Jiacun Wang and published by CRC Press. This book was released on 2016-04-19 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applicable to any problem that requires a finite number of solutions, finite state-based models (also called finite state machines or finite state automata) have found wide use in various areas of computer science and engineering. Handbook of Finite State Based Models and Applications provides a complete collection of introductory materials on fini

Download or read book Hidden Markov Models and Applications written by Nizar Bouguila and published by Springer Nature. This book was released on 2022-05-19 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and applications that consider HMMs. The authors discuss challenging problems that exist when considering HMMs for a specific task or application, such as estimation or selection, etc. The goal of this volume is to summarize the recent advances and modern approaches related to these problems. The book also reports advances on classic but difficult problems in HMMs such as inference and feature selection and describes real-world applications of HMMs from several domains. The book pertains to researchers and graduate students, who will gain a clear view of recent developments related to HMMs and their applications.

Download or read book Modelling and Applications in Mathematics Education written by Peter L. Galbraith and published by Springer Science & Business Media. This book was released on 2007-12-05 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims at showing the state-of-the-art in the field of modeling and applications in mathematics education. This is the first volume to do this. The book deals with the question of how key competencies of applications and modeling at the heart of mathematical literacy may be developed; with the roles that applications and modeling may play in mathematics teaching, making mathematics more relevant for students.

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Download or read book Handbook of Cancer Models with Applications written by W. Y. Tan and published by World Scientific. This book was released on 2008 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Composed of contributions from an international team of leading researchers, this book pulls together the most recent research results in the field of cancer modeling to provide readers with the most advanced mathematical models of cancer and their applications.Topics included in the book cover oncogenetic trees, stochastic multistage models of carcinogenesis, effects of ionizing radiation on cell cycle and genomic instability, induction of DNA damage by ionizing radiation and its repair, epigenetic cancer models, bystander effects of radiation, multiple pathway models of human colon cancer, and stochastic models of metastasis. The book also provides some important applications of cancer models to the assessment of cancer risk associated with various hazardous environmental agents, to cancer screening by MRI, and to drug resistance in cancer chemotherapy. An updated statistical design and analysis of xenograft experiments as well as a statistical analysis of cancer occult clinical data are also provided.The book will serve as a useful source of reference for researchers in biomathematics, biostatistics and bioinformatics; for clinical investigators and medical doctors employing quantitative methods to develop procedures for cancer diagnosis, prevention, control and treatment; and for graduate students.

Download or read book Business Enterprise Process and Technology Management Models and Applications written by Shankararaman, Venky and published by IGI Global. This book was released on 2012-03-31 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book generates a comprehensive overview of the recent advances in concepts, technologies, and applications that enable advanced business process management in various enterprises"--Provided by publisher.

Download or read book Mixture Models and Applications written by Nizar Bouguila and published by Springer. This book was released on 2019-08-13 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks that consider mixture models as their main tool. The chapters considers mixture models involving several interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the recent advances and modern approaches related to these problems. Each contributor presents novel research, a practical study, or novel applications based on mixture models, or a survey of the literature. Reports advances on classic problems in mixture modeling such as parameter estimation, model selection, and feature selection; Present theoretical and practical developments in mixture-based modeling and their importance in different applications; Discusses perspectives and challenging future works related to mixture modeling.