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  • Sách/Book

  • Precalculus

    • Authors: Sullivan, Michael (2023)

  • For courses in Precalculus. Prepare. Practice. Review. Michael Sullivan's time-tested approach focuses students on the fundamental skills they need for the course: preparing for class, practicing with homework, and reviewing the concepts.
  • Sách/Book

  • Skill in Mathematics: Algebra for JEE main and advanced

    • Authors: Dr. SK Goyal (2021)

  • Skill in Mathematics' series is prepared for JEE Main and Advanced papers2. It is a highly recommended textbook to develop a strong grounding in Algebra3. The book covers the entire syllabus into 11 chapters4. Each chapter includes a wide range of questions that are asked in the examinationsGood foundational grip is required in the Algebraic Methods, while you are preparing for JEE Mains & Advanced or any other engineering.
  • Sách/Book

  • Essential mathematics for economic analysis

    • Authors: Sydsæter, Knut (2021)

  • The subject matter that modern economics students are expected to master makes significant mathematical demands. This is true even of the less technical "applied" literature that students will be expected to read for courses in fields such as public finance, industrial organization, and labour economics, amongst several others. Indeed, the most relevant literature typically presumes familiarity with several important mathematical tools, especially calculus for functions of one and several variables, as well as a basic understanding of multivariable optimization problems with or without constraints. Linear algebra is also used to some extent in economic theory, and a great deal more in econometrics"--
  • Sách/Book

  • A first course in abstract algebra

    • Authors: Fraleigh, John B (2021)

  • This is an introduction to abstract algebra. It is anticipated that the students have studied calculus and probably linear algebra. However, these are primarily mathematical maturity prerequisites; subject matter from calculus and linear algebra appears mostly in illustrative examples and exercises. As in previous editions of the text, my aim remains to teach students as much about groups, rings, and fields as I can in a first course. For many students, abstract algebra is their first extended exposure to an axiomatic treatment of mathematics. Recognizing this, I have included extensive explanations concerning what we are trying to accomplish, how we are trying to do it, and why we choose these methods. Mastery of this text constitutes a firm foundation fo
  • Sách/Book

  • Data envelopment analysis : a comprehensive text with models, applications, references and DEA-solver software

    • Authors: William W. Cooper (2007)

  • This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.
  • Sách/Book

  • Statistics at square two : understanding modern statistical applications in medicine

    • Authors: Campbell, Michael J (2023)

  • In the sixteen years since the second edition of Statistics at Square Two was published, there have been many developments in statistical methodology and in methods of presenting statistics. MJC is pleased that his colleague Richard Jacques, who has considerable experience in more advanced statistical methods and teaching medical statistics to non- statisticians, has joined him as a co-author. Most of the examples have been updated and two new chapters have been added on meta-analysis and on time series analysis. In addition, reference is made to the many checklists which have appeared since the last edition to enable better reporting of research. This book is intended to build on the latest edition of Statistics at Square One."
  • Sách/Book

  • Linear Algebra with Applications

    • Authors: Leon, Steven J (2021)

  • The new 10thEdition ofLinear Algebra with Applications continuesto encourage a challenging and broad understanding of the subject. For thisedition, Steven Leon―one of the leading figures in the use of technology forlinear algebra―is joined by new co-author Lisette de Pillis of Harvey MuddCollege, who brings her passion for teaching and solving real-world problems tothis revision.
  • Sách/Book

  • An introduction to optimization with applications in machine learning and data analytics

    • Authors: Wheeler, Jeffrey Paul (2023)

  • The primary goal of this text is a practical one. Equipping students with the enough knowledge and creating an independent research platform, the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. The initial goal of this text is to develop marketable skill set for mathematics majors but also for students of engineering, computer science, economics, statistics, and business
  • Sách/Book

  • Even you can learn statistics and analytics : an easy to understand guide

    • Authors: Levine, David M (2022)

  • This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldnt learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel.
  • Sách/Book

  • Theory of multiobjective optimization

    • Authors: Tetsuzo Tanino; Hirotaka Nakayama; Yoshikazu Sawarag (1985)

  • In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a ...