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| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959 Kenneth Joseph Arrow, Samuel Karlin, Patrick Suppes, 1960 |
| mathematical methods in the social sciences: Readings in Mathematical Social Science Paul Felix Lazarsfeld, 1968 |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959 Kenneth Joseph Arrow, Samuel Karlin, Patrick Suppes, 1966 |
| mathematical methods in the social sciences: Sociodynamics Wolfgang Weidlich, 2006-07-07 Highly recommended. . . . This is an important book in putting the burgeoning field of sociodynamics on a solid footing.—Journal of Artificial Societies and Social Simulation This text deals with general modelling concepts in the social sciences, their applications, and their mathematical methods. The author's well-organized approach offers a clear, coherent introduction to terminology, approaches, and goals in modelling. Appropriate for advanced undergraduates and graduate students, it requires a solid background in algebra and calculus. The three-part treatment begins by addressing general modelling concepts, the second part provides applications, and the third discusses mathematical method. Topics include population dynamics, group interaction, political transitions, evolutionary economics, and urbanization. Guiding students through a series of practical applications that illustrate the methods' potential scope, the text concludes with a detailed look at mathematical methods. |
| mathematical methods in the social sciences: Computational and Mathematical Modeling in the Social Sciences Scott de Marchi, 2005-08-15 Offers an overview of mathematical modeling concentrating on game theory, statistics and computational modeling. |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959; Proceedings. Edited by Kenneth J. Arrow, Samuel Karlin (And) Patrick Suppes Stanford Symposium on Mathematical Methods in the Social Sciences, Stanford University, 1959, 1966 |
| mathematical methods in the social sciences: Mathematical Models in the Social Sciences John G. Kemeny, 1962 |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959 Kenneth Joseph Arrow, samuel Karlin, Patrick Suppes, 1966 |
| mathematical methods in the social sciences: Essential Mathematics for Political and Social Research Jeff Gill, 2006-04-24 More than ever before, modern social scientists require a basic level of mathematical literacy, yet many students receive only limited mathematical training prior to beginning their research careers. This textbook addresses this dilemma by offering a comprehensive, unified introduction to the essential mathematics of social science. Throughout the book the presentation builds from first principles and eschews unnecessary complexity. Most importantly, the discussion is thoroughly and consistently anchored in real social science applications, with more than 80 research-based illustrations woven into the text and featured in end-of-chapter exercises. Students and researchers alike will find this first-of-its-kind volume to be an invaluable resource.--BOOK JACKET. |
| mathematical methods in the social sciences: Mathematical Methods of the Social Sciences D. Berlinski, 1975 |
| mathematical methods in the social sciences: Basic Math for Social Scientists Timothy Hagle, 1996-03-01 Aimed at providing readers who want a quick refresher course in mathematics with an informal review, Timothy M. Hagle′s volume offers dozens of worked-out examples of such mathematical concepts as algebra sets, limits, continuity, differential calculus, multivariate functions, partial derivatives, integral calculus, and matrix algebra. In addition, Hagle provides problem sets so that readers can practice their grasp of standard mathematical procedures (answers to these problem sets are contained in the appendixes). Written in a friendly style, Basic Math for Social Scientists: Problems and Solutions provides readers with an informal approach to mathematical procedures without proofs. |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959. Proceedings of the First Stanford Symposium. Edited by Kenneth J. Arrow, Samuel Karlin, Patrick Suppes Leland Stanford Junior University (STANFORD, California). Stanford Symposium on Mathematical Methods in the Social Sciences, Kenneth Joseph Arrow, Samuel Karlin, Patrick SUPPES, 1960 |
| mathematical methods in the social sciences: Mathematical Modeling of Social Relationships Urszula Strawinska-Zanko, Larry S. Liebovitch, 2018-06-07 This edited volume presents examples of social science research projects that employ new methods of quantitative analysis and mathematical modeling of social processes. This book presents the fascinating areas of empirical and theoretical investigations that use formal mathematics in a way that is accessible for individuals lacking extensive expertise but still desiring to expand their scope of research methodology and add to their data analysis toolbox. Mathematical Modeling of Social Relationships professes how mathematical modeling can help us understand the fundamental, compelling, and yet sometimes complicated concepts that arise in the social sciences. This volume will appeal to upper-level students and researchers in a broad area of fields within the social sciences, as well as the disciplines of social psychology, complex systems, and applied mathematics. |
| mathematical methods in the social sciences: Mathematical methods in the social sciences ed. by a., k. and s Kenneth Arrow, Samuel Karlin, Patrick Suppes, Stanford symposium, 1. proceedings, 1960 |
| mathematical methods in the social sciences: Quantitative Methods for the Social Sciences Daniel Stockemer, 2018-11-19 This textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences. |
| mathematical methods in the social sciences: Mathematical Modeling in Social Sciences and Engineering Juan Carlos Cortés López, Lucas Antonio Jodar Sanchez, 2014 This book is devoted to the power of mathematical modelling to give an answer to a broad diversity of real problems including medicine, finance, social behavioural problems and many engineering problems. Mathematical modelling in social sciences is very recent and comes with special challenges such as the difficulty to manage human behaviour, the role of the model hypothesis with the objectivity/subjectivity and the proper understanding of the conclusions. In this book, the reader will find several behavioural mathematical models that in fact may be understood as the so-called epidemiological models in the sense that they deal with populations instead of individuals. |
| mathematical methods in the social sciences: Mathematical Methods and Models in Biomedicine Urszula Ledzewicz, Heinz Schättler, Avner Friedman, Eugene Kashdan, 2012-10-20 Mathematical biomedicine is a rapidly developing interdisciplinary field of research that connects the natural and exact sciences in an attempt to respond to the modeling and simulation challenges raised by biology and medicine. There exist a large number of mathematical methods and procedures that can be brought in to meet these challenges and this book presents a palette of such tools ranging from discrete cellular automata to cell population based models described by ordinary differential equations to nonlinear partial differential equations representing complex time- and space-dependent continuous processes. Both stochastic and deterministic methods are employed to analyze biological phenomena in various temporal and spatial settings. This book illustrates the breadth and depth of research opportunities that exist in the general field of mathematical biomedicine by highlighting some of the fascinating interactions that continue to develop between the mathematical and biomedical sciences. It consists of five parts that can be read independently, but are arranged to give the reader a broader picture of specific research topics and the mathematical tools that are being applied in its modeling and analysis. The main areas covered include immune system modeling, blood vessel dynamics, cancer modeling and treatment, and epidemiology. The chapters address topics that are at the forefront of current biomedical research such as cancer stem cells, immunodominance and viral epitopes, aggressive forms of brain cancer, or gene therapy. The presentations highlight how mathematical modeling can enhance biomedical understanding and will be of interest to both the mathematical and the biomedical communities including researchers already working in the field as well as those who might consider entering it. Much of the material is presented in a way that gives graduate students and young researchers a starting point for their own work. |
| mathematical methods in the social sciences: A Mathematical Primer for Social Statistics John Fox, 2009 The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods |
| mathematical methods in the social sciences: Quantitative Social Science Kosuke Imai, Lori D. Bougher, 2021-03-16 The Stata edition of the groundbreaking textbook on data analysis and statistics for the social sciences and allied fields Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as business, economics, education, political science, psychology, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the Stata statistical software and interpret the results—it emphasizes hands-on learning, not paper-and-pencil statistics. More than fifty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in classrooms around the world, this one-of-a-kind textbook features numerous additional data analysis exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including business, economics, education, psychology, political science, sociology, public policy, and data science Provides hands-on instruction using Stata, not paper-and-pencil statistics Includes more than fifty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides |
| mathematical methods in the social sciences: Mathematical Methods in Science and Engineering Masud Mansuripur, 2019-10-15 Mathematical Methods in Science and Engineering: Applications in Optics and Photonics helps students build a conceptual appreciation for critical mathematical methods, as well as the physical feel and intuition for select mathematical ideas. Throughout the text, examples are provided from the field of optics and photonics to clarify key concepts. The book features 13 targeted chapters that begin with a brief introduction to the topical area and then dive direc |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959 Kenneth Joseph Arrow, 1960 |
| mathematical methods in the social sciences: Social Science Research Anol Bhattacherjee, 2012-03-16 This book is designed to introduce doctoral and graduate students to the process of scientific research in the social sciences, business, education, public health, and related disciplines. |
| mathematical methods in the social sciences: Mathematics in Science and Technology A. H. Siddiqi, R. C. Singh, Pammy Manchanda, 2011 This unique volume presents reviews of research in several important areas of applications of mathematical concepts to science and technology, for example applications of inverse problems and wavelets to real world systems. The book provides a comprehensive overview of current research of several outstanding scholars engaged in diverse fields such as complexity theory, vertex coupling in quantum graphs, mixing of substances by turbulence, network dynamics and architecture, processes with rate ? independent hysteresis, numerical analysis of Hamilton Jacobi ? Bellman equations, simulations of complex stochastic differential equations, optimal flow control, shape optimal flow control, shape optimization and aircraft designing, mathematics of brain, nanotechnology and DNA structure and mathematical models of environmental problems. The volume also contains contributory talks based on current researches of comparatively young researchers participating in the conference. |
| mathematical methods in the social sciences: Mathematical and Computational Modeling Roderick Melnik, 2015-05-21 Mathematical and Computational Modeling Illustrates the application of mathematical and computational modeling in a variety of disciplines With an emphasis on the interdisciplinary nature of mathematical and computational modeling, Mathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts features chapters written by well-known, international experts in these fields and presents readers with a host of state-of-theart achievements in the development of mathematical modeling and computational experiment methodology. The book is a valuable guide to the methods, ideas, and tools of applied and computational mathematics as they apply to other disciplines such as the natural and social sciences, engineering, and technology. The book also features: Rigorous mathematical procedures and applications as the driving force behind mathematical innovation and discovery Numerous examples from a wide range of disciplines to emphasize the multidisciplinary application and universality of applied mathematics and mathematical modeling Original results on both fundamental theoretical and applied developments in diverse areas of human knowledge Discussions that promote interdisciplinary interactions between mathematicians, scientists, and engineers Mathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts is an ideal resource for professionals in various areas of mathematical and statistical sciences, modeling and simulation, physics, computer science, engineering, biology and chemistry, and industrial and computational engineering. The book also serves as an excellent textbook for graduate courses in mathematical modeling, applied mathematics, numerical methods, operations research, and optimization. |
| mathematical methods in the social sciences: Mathematical Methods of Game and Economic Theory Jean-Pierre Aubin, 2007-01-01 Mathematical economics and game theory approached with the fundamental mathematical toolbox of nonlinear functional analysis are the central themes of this text. Both optimization and equilibrium theories are covered in full detail. The book's central application is the fundamental economic problem of allocating scarce resources among competing agents, which leads to considerations of the interrelated applications in game theory and the theory of optimization. Mathematicians, mathematical economists, and operations research specialists will find that it provides a solid foundation in nonlinear functional analysis. This text begins by developing linear and convex analysis in the context of optimization theory. The treatment includes results on the existence and stability of solutions to optimization problems as well as an introduction to duality theory. The second part explores a number of topics in game theory and mathematical economics, including two-person games, which provide the framework to study theorems of nonlinear analysis. The text concludes with an introduction to non-linear analysis and optimal control theory, including an array of fixed point and subjectivity theorems that offer powerful tools in proving existence theorems. |
| mathematical methods in the social sciences: Mathematical Methods for the Physical Sciences K. F. Riley, 1974-10-03 Designed for first and second year undergraduates at universities and polytechnics, as well as technical college students. |
| mathematical methods in the social sciences: Mathematical Methods in Social Science David J. Bartholomew, 1981 |
| mathematical methods in the social sciences: A Mathematics Course for Political and Social Research Will H. Moore, David A. Siegel, 2013-08-11 Political science and sociology increasingly rely on mathematical modeling and sophisticated data analysis, and many graduate programs in these fields now require students to take a math camp or a semester-long or yearlong course to acquire the necessary skills. Available textbooks are written for mathematics or economics majors, and fail to convey to students of political science and sociology the reasons for learning often-abstract mathematical concepts. A Mathematics Course for Political and Social Research fills this gap, providing both a primer for math novices in the social sciences and a handy reference for seasoned researchers. The book begins with the fundamental building blocks of mathematics and basic algebra, then goes on to cover essential subjects such as calculus in one and more than one variable, including optimization, constrained optimization, and implicit functions; linear algebra, including Markov chains and eigenvectors; and probability. It describes the intermediate steps most other textbooks leave out, features numerous exercises throughout, and grounds all concepts by illustrating their use and importance in political science and sociology. Uniquely designed and ideal for students and researchers in political science and sociology Uses practical examples from political science and sociology Features Why Do I Care? sections that explain why concepts are useful Includes numerous exercises Complete online solutions manual (available only to professors, email david.siegel at duke.edu, subject line Solution Set) Selected solutions available online to students |
| mathematical methods in the social sciences: Mathematical Applications for the Management, Life, and Social Sciences Ronald J. Harshbarger, James J. Reynolds, 2012-01-01 MATHEMATICAL APPLICATIONS FOR THE MANAGEMENT, LIFE, AND SOCIAL SCIENCES, 10th Edition, is intended for a two-semester applied calculus or combined finite mathematics and applied calculus course. The book's concept-based approach, multiple presentation methods, and interesting and relevant applications keep students who typically take the course--business, economics, life sciences, and social sciences majors--engaged in the material. This edition broadens the book's real-life context by adding a number of environmental science and economic applications. The use of modeling has been expanded, with modeling problems now clearly labeled in the examples. Also included in the Tenth Edition is a brief review of algebra to prepare students with different backgrounds for the material in later chapters. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |
| mathematical methods in the social sciences: Mathematical Methods in the Social and Managerial Sciences Patrick Hayes, 1975 |
| mathematical methods in the social sciences: MATHEMATICAL METHODS IN THE SOCIAL SCIENCES- PROCEEDINGS OF A SEMINAR- INSTITUTE OF PHYSICS AND MATHEMATICS OF THE LITHUANIAN ACADEMY OF SCIENCES- IN RUSSIAN. , |
| mathematical methods in the social sciences: Mathematical Methods in Engineering and Applied Sciences Taylor & Francis Group, 2021-09-30 This book covers tools and techniques used for developing mathematical methods and modelling related to real-life situations. It brings forward significant aspects of mathematical research by using different mathematical methods such as analytical, computational, and numerical with relevance or applications in engineering and applied sciences. |
| mathematical methods in the social sciences: Mathematical Methods in Statistics David Freedman, David Lane, 1981 |
| mathematical methods in the social sciences: Mathematical Methods in the Physical Sciences Mary L. Boas, 2006 Market_Desc: · Physicists and Engineers· Students in Physics and Engineering Special Features: · Covers everything from Linear Algebra, Calculus, Analysis, Probability and Statistics, to ODE, PDE, Transforms and more· Emphasizes intuition and computational abilities· Expands the material on DE and multiple integrals· Focuses on the applied side, exploring material that is relevant to physics and engineering· Explains each concept in clear, easy-to-understand steps About The Book: The book provides a comprehensive introduction to the areas of mathematical physics. It combines all the essential math concepts into one compact, clearly written reference. This book helps readers gain a solid foundation in the many areas of mathematical methods in order to achieve a basic competence in advanced physics, chemistry, and engineering. |
| mathematical methods in the social sciences: Mathematical Methods of Classical Mechanics V.I. Arnol'd, 2013-04-09 In this text, the author constructs the mathematical apparatus of classical mechanics from the beginning, examining all the basic problems in dynamics, including the theory of oscillations, the theory of rigid body motion, and the Hamiltonian formalism. This modern approch, based on the theory of the geometry of manifolds, distinguishes iteself from the traditional approach of standard textbooks. Geometrical considerations are emphasized throughout and include phase spaces and flows, vector fields, and Lie groups. The work includes a detailed discussion of qualitative methods of the theory of dynamical systems and of asymptotic methods like perturbation techniques, averaging, and adiabatic invariance. |
| mathematical methods in the social sciences: Mathematical Models for Society and Biology Edward Beltrami, 2013-06-19 Mathematical Models for Society and Biology, 2e, is a useful resource for researchers, graduate students, and post-docs in the applied mathematics and life science fields. Mathematical modeling is one of the major subfields of mathematical biology. A mathematical model may be used to help explain a system, to study the effects of different components, and to make predictions about behavior. Mathematical Models for Society and Biology, 2e, draws on current issues to engagingly relate how to use mathematics to gain insight into problems in biology and contemporary society. For this new edition, author Edward Beltrami uses mathematical models that are simple, transparent, and verifiable. Also new to this edition is an introduction to mathematical notions that every quantitative scientist in the biological and social sciences should know. Additionally, each chapter now includes a detailed discussion on how to formulate a reasonable model to gain insight into the specific question that has been introduced. - Offers 40% more content – 5 new chapters in addition to revisions to existing chapters - Accessible for quick self study as well as a resource for courses in molecular biology, biochemistry, embryology and cell biology, medicine, ecology and evolution, bio-mathematics, and applied math in general - Features expanded appendices with an extensive list of references, solutions to selected exercises in the book, and further discussion of various mathematical methods introduced in the book |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences, 1959 Kenneth J. Arrow, Samuel Karlin, Patrick Suppes, 1960 |
| mathematical methods in the social sciences: Advanced Mathematical Methods Adam Ostaszewski, 1990 This text is a self-contained second course on mathematical methods dealing with topics in linear algebra and multivariate calculus that can be applied to statistics. |
| mathematical methods in the social sciences: Mathematical Methods in the Social Sciences , 1966 |
| mathematical methods in the social sciences: Measurement Theory and Applications for the Social Sciences Deborah L. Bandalos, 2017-12-12 Which types of validity evidence should be considered when determining whether a scale is appropriate for a given measurement situation? What about reliability evidence? Using clear explanations illustrated by examples from across the social and behavioral sciences, this engaging text prepares students to make effective decisions about the selection, administration, scoring, interpretation, and development of measurement instruments. Coverage includes the essential measurement topics of scale development, item writing and analysis, and reliability and validity, as well as more advanced topics such as exploratory and confirmatory factor analysis, item response theory, diagnostic classification models, test bias and fairness, standard setting, and equating. End-of-chapter exercises (with answers) emphasize both computations and conceptual understanding to encourage readers to think critically about the material. The companion website (www.guilford.com/bandalos-materials) provides annotated examples, syntax, and datasets in both SPSS and SAS (for most chapters), so that readers can redo the analyses in each chapter. |
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Mathematics is a field of study that discovers and organizes methods, theories and theorems that are …
Wolfram Mathematica: Modern Technical Computing
Mathematica is built to provide industrial-strength capabilities—with robust, efficient algorithms across …
Mathematics | Definition, History, & Importance | Brita…
Apr 30, 2025 · mathematics, the science of structure, order, and relation that has evolved from elemental …
Wolfram MathWorld: The Web's Most Extensive Mathematics …
May 22, 2025 · Comprehensive encyclopedia of mathematics with 13,000 detailed entries. Continually …
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