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| mathematical social sciences: Readings in Mathematical Social Science Paul Felix Lazarsfeld, 1968 |
| mathematical social sciences: Mathematics for Social Scientists Jonathan Kropko, 2016 |
| mathematical 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 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 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 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 social sciences: Maths for Social Sciences Lorenzo Peccati, Mauro D'Amico, Margherita Cigola, 2019-01-14 This book is aimed at students in social sciences programs that include some course in quantitative methods. Stats for social sciences is frequently the subject of textbooks, while maths for social sciences is often neglected: monographs on specific themes (like, for instance, social choice systems or game theory applications) are available, but they do not adequately cover the topic in general. This textbook stems from the Bocconi University’s new Bachelor in Government, which was launched in 2015, and is intended for undergraduate students who do not exclude maths from their toolbox. It discusses various concrete applications in political economics, political science, sociology, and demography and explores topics like Grexit, Macron’s success, immigration effects and the Arab Spring. |
| mathematical 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 social sciences: Mathematical Models in the Social Sciences John G. Kemeny, 1962 |
| mathematical 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 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 social sciences: Nonlinear Dynamics, Mathematical Biology, And Social Science Joshua M. Epstein, 2018-03-08 This book is based on a series of lectures on mathematical biology, the essential dynamics of complex and crucially important social systems, and the unifying power of mathematics and nonlinear dynamical systems theory. |
| mathematical 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 social sciences: Game Theory for the Social Sciences Herve Moulin, 1986-10-01 The second edition of Herve Moulin's highly successful book outlines the fundamental concepts of game theory—one of the most provocative and fruitful applications of mathematics to the human sciences—and demonstrates its uses in economic and political discourse. Thoroughly revised, and now published with an accompanying workbook of 89 exercises, this rigorous yet accessible test explains the uses of game theory in largely nontechnical terms. Moulin carefully discusses the behavioral scenarios underlying the various equilibrium concepts. He provides a self-contained exposition of basic equilibrium concepts for strategic games: perfect (sophisticated) equilibrium, Nash's noncooperative example, Aumann's strong and correlated example, and several versions of the core. The author is concerned less with mathematical refinements than with helping the reader understand the strategic stories backing these concepts. HIs examples therefore give a fair account of the current game models used in economics, politics, and sociology. Addressed here are oligopoly theory, the provision of public gtoods, auctions, voting procedures, and cost allocation problems, as well as the classic prisoner's dilemma, tic-tac-toe, and Marienbad games. Extremely popular in its original French edition and in its first English version, Moulin's excellent introductory text is now, more than ever, the book to answer the essential questions about the application of game theory to the social sciences. |
| mathematical social sciences: Readings in Mathematical Social Science Paul F. Lazarsfeld, Neil W. Henry, 1966 |
| mathematical social sciences: Linear Algebra for Social Sciences Menahem E. Yaari, 1971 |
| mathematical 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 social sciences: Data Analysis for Social Science Elena Llaudet, Kosuke Imai, 2023 Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors-- |
| mathematical social sciences: Introductory Mathematical Analysis Ernest F. Haeussler, Richard S. Paul, Richard J. Wood, 2007 For courses in Mathematics for Business and Mathematical Methods in Business.This classic text continues to provide a mathematical foundation for students in business, economics, and the life and social sciences. Abundant applications cover such diverse areas as business, economics, biology, medicine, sociology, psychology, ecology, statistics, earth science, and archaeology. Its depth and completeness of coverage enables instructors to tailor their courses to students' needs. The authors frequently employ novel derivations that are not widespread in other books at this level. The Twelfth Edition has been updated to make the text even more student-friendly and easy to understand. |
| mathematical 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 social sciences: Soft Computing Techniques in Engineering, Health, Mathematical and Social Sciences Pradip Debnath, S. A. Mohiuddine, 2021-07-15 Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics. |
| mathematical social sciences: Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences Giovanni Naldi, Lorenzo Pareschi, Giuseppe Toscani, 2010-08-12 Using examples from finance and modern warfare to the flocking of birds and the swarming of bacteria, the collected research in this volume demonstrates the common methodological approaches and tools for modeling and simulating collective behavior. The topics presented point toward new and challenging frontiers of applied mathematics, making the volume a useful reference text for applied mathematicians, physicists, biologists, and economists involved in the modeling of socio-economic systems. |
| mathematical social sciences: The Dynamics and Evolution of Social Systems Jürgen Klüver, 2000-07-31 The central topic of this book is the mathematical analysis of social systems, understood in the following rather classical way: social systems consist of social actors who interact according to specific rules of interactions; the dynamics of social systems is then the consequences of these interactions, viz., the self-organization of social systems. According to particular demands of their environment, social systems are able to behave in an adaptive manner, that is they can change their rules of interaction by certain meta rules and thus generate a meta dynamics. It is possible to model and analyse mathematically both dynamics and meta dynamics, using cellular automata and genetic algorithms. These tools allow social systems theory to be carried through as precisely as the theories of natural systems, a feat that has not previously been possible. Readership: Researchers and graduate students in the fields of theoretical sociology and social and general systems theory and other interested scientists. No specialised knowledge of mathematics and/or computer science is required. |
| mathematical social sciences: Mathematical Modelling in Health, Social and Applied Sciences Hemen Dutta, 2020-02-29 This book discusses significant research findings in the field of mathematical modelling, with particular emphasis on important applied-sciences, health, and social issues. It includes topics such as model on viral immunology, stochastic models for the dynamics of influenza, model describing the transmission of dengue, model for human papillomavirus (HPV) infection, prostate cancer model, realization of economic growth by goal programming, modelling of grazing periodic solutions in discontinuous systems, modelling of predation system, fractional epidemiological model for computer viruses, and nonlinear ecological models. A unique addition in the proposed areas of research and education, this book is a valuable resource for graduate students, researchers and educators associated with the study of mathematical modelling of health, social and applied-sciences issues. Readers interested in applied mathematics should also find this book valuable. |
| mathematical social sciences: Chaos Theory in the Social Sciences L. Douglas Kiel, Euel W. Elliott, 2009-11-10 Chaos Theory in the Social Sciences: Foundations and Applications offers the most recent thinking in applying the chaos paradigm to the social sciences. The book explores the methodological techniques--and their difficulties--for determining whether chaotic processes may in fact exist in a particular instance and examines implications of chaos theory when applied specifically to political science, economics, and sociology. The contributors to the book show that no single technique can be used to diagnose and describe all chaotic processes and identify the strengths and limitations of a variety of approaches. The essays in this volume consider the application of chaos theory to such diverse phenomena as public opinion, the behavior of states in the international arena, the development of rational economic expectations, and long waves. Contributors include Brian J. L. Berry, Thad Brown, Kenyon B. DeGreene, Dimitrios Dendrinos, Euel Elliott, David Harvey, L. Ted Jaditz, Douglas Kiel, Heja Kim, Michael McBurnett, Michael Reed, Diana Richards, J. Barkley Rosser, Jr., and Alvin M. Saperstein. L. Douglas Kiel and Euel W. Elliott are both Associate Professors of Government, Politics, and Political Economy, University of Texas at Dallas. |
| mathematical social sciences: Mathematical Models of Social Evolution Richard McElreath, Robert Boyd, 2007-03-15 Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field. Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own. |
| mathematical social sciences: Introduction to Math Analysis Ernest F. Haeussler, Richard S. Paul, Laurel Technical Services, 1999 |
| mathematical 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 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 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. |
| mathematical social sciences: What's Happening in the Mathematical Sciences Barry Cipra, Mathematicians like to point out that mathematics is universal. In spite of this, most people continue to view it as either mundane (balancing a checkbook) or mysterious (cryptography). This fifth volume of the What's Happening series contradicts that view by showing that mathematics is indeed found everywhere-in science, art, history, and our everyday lives. Here is some of what you'll find in this volume: Mathematics and Science Mathematical biology: Mathematics was key tocracking the genetic code. Now, new mathematics is needed to understand the three-dimensional structure of the proteins produced from that code. Celestial mechanics and cosmology: New methods have revealed a multitude of solutions to the three-body problem. And other new work may answer one of cosmology'smost fundamental questions: What is the size and shape of the universe? Mathematics and Everyday Life Traffic jams: New models are helping researchers understand where traffic jams come from-and maybe what to do about them! Small worlds: Researchers have found a short distance from theory to applications in the study of small world networks. Elegance in Mathematics Beyond Fermat's Last Theorem: Number theorists are reaching higher ground after Wiles' astounding 1994 proof: new developments inthe elegant world of elliptic curves and modular functions. The Millennium Prize Problems: The Clay Mathematics Institute has offered a million dollars for solutions to seven important and difficult unsolved problems. These are just some of the topics of current interest that are covered in thislatest volume of What's Happening in the Mathematical Sciences. The book has broad appeal for a wide spectrum of mathematicians and scientists, from high school students through advanced-level graduates and researchers. |
| mathematical social sciences: Mathematical Frontiers Of The Social And Policy Sciences Loren Cobb, Robert M Thrall, 1981 |
| mathematical social sciences: Mathematics and the Social Sciences James Clyde Charlesworth, American Academy of Political and Social Science, 1963 |
| mathematical social sciences: Mathematical Modelling D. N. P. Murthy, N. W. Page, Ervin Y. Rodin, 1990 |
| mathematical social sciences: College Mathematics for the Managerial, Life, and Social Sciences Soo Tang Tan, 2004-02-01 With clear writing, effective integration of technology tools, a problem-solving approach, and relevant applications, author Soo Tan takes the intimidation out of college mathematics. Throughout each chapter, you'll see mathematics as it applies in the real world - from investment clubs and online travel to the market for cholesterol-reducing drugs and Starbucks' annual sales. Helpful features include: using technology sections; self-check exercises and remarks, hints and cautions. |
| mathematical 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 social sciences: Mathematical Social Sciences , 1982-07 |
| mathematical social sciences: Social Sciences as Sorcery Stanislav Andreski, 1974 |
| mathematical social sciences: Introduction to Mathematical Sociology James S. Coleman, 1964 |
| mathematical social sciences: The Mathematical Sciences , 1969 |
Mathematics - Wikipedia
Mathematics is a field of study that discovers and organizes methods, theories and theorems that are developed and proved for the needs of empirical sciences and mathematics itself.
Wolfram Mathematica: Modern Technical Computing
Mathematica is built to provide industrial-strength capabilities—with robust, efficient algorithms across all areas, capable of handling large-scale problems, with parallelism, GPU computing …
Mathematics | Definition, History, & Importance | Britannica
Apr 30, 2025 · mathematics, the science of structure, order, and relation that has evolved from elemental practices of counting, measuring, and describing the shapes of objects. It deals with …
Wolfram MathWorld: The Web's Most Extensive Mathematics …
May 22, 2025 · Comprehensive encyclopedia of mathematics with 13,000 detailed entries. Continually updated, extensively illustrated, and with interactive examples.
Wolfram|Alpha: Computational Intelligence
Compute answers using Wolfram's breakthrough technology & knowledgebase, relied on by millions of students & professionals. For math, science, nutrition, history, geography, …
MATHEMATICAL Definition & Meaning - Merriam-Webster
The meaning of MATHEMATICAL is of, relating to, or according with mathematics. How to use mathematical in a sentence.
Mathematics - Encyclopedia of Mathematics
Mar 30, 2012 · In the 17th century new questions in natural science and technology compelled mathematicians to concentrate their attention on the creation of methods to allow the …
MATHEMATICAL | English meaning - Cambridge Dictionary
mathematical formula The researchers used a mathematical formula to calculate the total population number. mathematical problem It was a mathematical problem that he could not …
Mathematical - definition of mathematical by The Free Dictionary
mathematical - of or pertaining to or of the nature of mathematics; "a mathematical textbook"; "slide rules and other mathematical instruments"; "a mathematical solution to a problem"; …
What is Mathematics? – Mathematical Association of America
Math is about getting the right answers, and we want kids to learn to think so they get the right answer. My reaction was visceral and immediate. “This is wrong. The emphasis needs to be …
Mathematics - Wikipedia
Mathematics is a field of study that discovers and organizes methods, theories and theorems that are developed and proved for the needs of empirical sciences and mathematics itself.
Wolfram Mathematica: Modern Technical Computing
Mathematica is built to provide industrial-strength capabilities—with robust, efficient algorithms across all areas, capable of handling large-scale problems, with parallelism, GPU computing …
Mathematics | Definition, History, & Importance | Britannica
Apr 30, 2025 · mathematics, the science of structure, order, and relation that has evolved from elemental practices of counting, measuring, and describing the shapes of objects. It deals with …
Wolfram MathWorld: The Web's Most Extensive Mathematics …
May 22, 2025 · Comprehensive encyclopedia of mathematics with 13,000 detailed entries. Continually updated, extensively illustrated, and with interactive examples.
Wolfram|Alpha: Computational Intelligence
Compute answers using Wolfram's breakthrough technology & knowledgebase, relied on by millions of students & professionals. For math, science, nutrition, history, geography, …
MATHEMATICAL Definition & Meaning - Merriam-Webster
The meaning of MATHEMATICAL is of, relating to, or according with mathematics. How to use mathematical in a sentence.
Mathematics - Encyclopedia of Mathematics
Mar 30, 2012 · In the 17th century new questions in natural science and technology compelled mathematicians to concentrate their attention on the creation of methods to allow the …
MATHEMATICAL | English meaning - Cambridge Dictionary
mathematical formula The researchers used a mathematical formula to calculate the total population number. mathematical problem It was a mathematical problem that he could not …
Mathematical - definition of mathematical by The Free Dictionary
mathematical - of or pertaining to or of the nature of mathematics; "a mathematical textbook"; "slide rules and other mathematical instruments"; "a mathematical solution to a problem"; …
What is Mathematics? – Mathematical Association of America
Math is about getting the right answers, and we want kids to learn to think so they get the right answer. My reaction was visceral and immediate. “This is wrong. The emphasis needs to be …
