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| basic math for social scientists: 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. |
| basic math for social scientists: Basic Math for Social Scientists Timothy Hagle, 1996-03 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. |
| basic math for social scientists: Basic Math for Social Scientists Timothy Hagle, 1995-06-29 A review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences is presented in this volume. The author begins with an algebra review featuring sets and combinations and then discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus, multivariate functions, partial derivatives, and integral calculus. Finally the book deals with matrix algebra. Packed with helpful definitions, equations, examples and alternative notations, the book also includes a useful appendix of common mathematical symbols and Greek letters. |
| basic math for social scientists: 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. |
| basic math for social scientists: Mathematics for Social Scientists Jonathan Kropko, 2016 |
| basic math for social scientists: Basic Math for Social Scientists Timothy M. Hagle, 1995 Taking an informal approach, Hagle presents a review of the basic mathematical concepts that underlie most quantitative analysis in the social sciences. After an algebra review featuring sets and combinations, Hagle discusses limits and continuity. Calculus is presented next, with an introduction to differential calculus. Multivariate functions, partial derivatives and integral calculus are discussed; the author concludes with a discussion of matrix algebra. Aimed at readers who have taken one or two courses in algebra, this volume is packed with helpful definitions, equations, and examples as well as alternative notations. A useful appendix of common math symbol and Greek letters is also included. Learn more about The Little Green Book--QASS Series! |
| basic math for social scientists: 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 |
| basic math for social scientists: 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. |
| basic math for social scientists: 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. |
| basic math for social scientists: Mathematics for Social Justice: Resources for the College Classroom Gizem Karaali, Lily S. Khadjavi, 2019-07-09 Mathematics for Social Justice offers a collection of resources for mathematics faculty interested in incorporating questions of social justice into their classrooms. The book begins with a series of essays from instructors experienced in integrating social justice themes into their pedagogy; these essays contain political and pedagogical motivations as well as nuts-and-bolts teaching advice. The heart of the book is a collection of fourteen classroom-tested modules featuring ready-to-use activities and investigations for the college mathematics classroom. The mathematical tools and techniques used are relevant to a wide variety of courses including college algebra, math for the liberal arts, calculus, differential equations, discrete mathematics, geometry, financial mathematics, and combinatorics. The social justice themes include human trafficking, income inequality, environmental justice, gerrymandering, voting methods, and access to education. The volume editors are leaders of the national movement to include social justice material into mathematics teaching. Gizem Karaali is Associate Professor of Mathematics at Pomona College. She is one of the founding editors of The Journal of Humanistic Mathematics, and an associate editor for The Mathematical Intelligencer and Numeracy ; she also serves on the editorial board of the MAA's Carus Mathematical Monographs. Lily Khadjavi is Associate Professor of Mathematics at Loyola Marymount University and is a past co-chair of the Infinite Possibilities Conference. She has served on the boards of Building Diversity in Science, the Barbara Jordan-Bayard Rustin Coalition, and the Harvard Gender and Sexuality Caucus. |
| basic math for social scientists: Basic Statistics for Social Research Robert A. Hanneman, Augustine J. Kposowa, Mark D. Riddle, 2012-12-04 A core statistics text that emphasizes logical inquiry, not math Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to understand (and do) social research. Its use of mathematics and theory are deliberately limited, as the authors focus on the use of concepts and tools of statistics in the analysis of social science data, rather than on the mathematical and computational aspects. Research questions and applications are taken from a wide variety of subfields in sociology, and each chapter is organized around one or more general ideas that are explained at its beginning and then applied in increasing detail in the body of the text. Each chapter contains instructive features to aid students in understanding and mastering the various statistical approaches presented in the book, including: Learning objectives Check quizzes after many sections and an answer key at the end of the chapter Summary Key terms End-of-chapter exercises SPSS exercises (in select chapters) Ancillary materials for both the student and the instructor are available and include a test bank for instructors and downloadable video tutorials for students. |
| basic math for social scientists: 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 |
| basic math for social scientists: 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-- |
| basic math for social scientists: Math for Scientists Natasha Maurits, Branislava Ćurčić-Blake, 2017-08-26 This book reviews math topics relevant to non-mathematics students and scientists, but which they may not have seen or studied for a while. These math issues can range from reading mathematical symbols, to using complex numbers, dealing with equations involved in calculating medication equivalents, the General Linear Model (GLM) used in e.g. neuroimaging analysis, finding the minimum of a function, independent component analysis, or filtering approaches. Almost every student or scientist, will at some point run into mathematical formulas or ideas in scientific papers that may be hard to understand, given that formal math education may be some years ago. In this book we will explain the theory behind many of these mathematical ideas and expressions and provide readers with the tools to better understand them. We will revisit high school mathematics and extend and relate this to the mathematics you need to understand the math you may encounter in the course of your research. This book will help you understand the math and formulas in the scientific papers you read. To achieve this goal, each chapter mixes theory with practical pen-and-paper exercises such that you (re)gain experience with solving math problems yourself. Mnemonics will be taught whenever possible. To clarify the math and help readers apply it, each chapter provides real-world and scientific examples. |
| basic math for social scientists: 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. |
| basic math for social scientists: Quantitative Geography Richard Harris, 2016-09-13 Numerical data are everywhere. Charts and statistics appear not just in geography journals but also in the media, in public policy, and in business and commerce too. To engage with quantitative geography, we must engage with the quantitative methods used to collect, analyse, present and interpret these data. Quantitative Geography: The Basics is the perfect introduction for undergraduates beginning any quantitative methods course. Written in short, user-friendly chapters with full-colour diagrams, the book guides the reader through a wide range of topics from the basic to the more advanced, including: Statistics Maths Graphics Models Mapping and GIS R Closely aligned with the Q-Step quantitative social science programme, Quantitative Geography: The Basics is the ideal starting point for understanding and exploring this fundamental area of Geography. |
| basic math for social scientists: Mathematics And Science Ronald E Mickens, 1990-08-23 The purpose of this review volume is to present the opinions of a number of distinguished individuals who have given careful thought as to why mathematics is so “unreasonably effective” when applied to the analysis of the natural sciences. |
| basic math for social scientists: Regression Analysis for the Social Sciences Rachel A. Gordon, 2015 This book provides graduate students in the social sciences with the basic skills that they need in order to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: - interweaving the teaching of statistical concepts with examples developed for the course from publicly available social science data or drawn from the literature; - thorough integration of teaching statistical theory with teaching data processing and analysis using Stata; - use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set-- |
| basic math for social scientists: Maximum Likelihood for Social Science Michael D. Ward, John S. Ahlquist, 2018-11-22 Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation. |
| basic math for social scientists: Mathematics for Social Scientists Jonathan Kropko, 2015-09-09 Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students’ confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students’ reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations. |
| basic math for social scientists: 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. |
| basic math for social scientists: Introduction to Mathematics for Life Scientists E. Batschelet, 2012-12-06 A few decades ago mathematics played a modest role in life sciences. Today, however, a great variety of mathematical methods is applied in biology and medicine. Practically every mathematical procedure that is useful in physics, chemistry, engineering, and economics has also found an important application in the life sciences. The past and present training of life scientists does by no means reflect this development. However, the impact ofthe fast growing number of applications of mathematical methods makes it indispensable that students in the life sciences are offered a basic training in mathematics, both on the undergraduate and the graduate level. This book is primarily designed as a textbook for an introductory course. Life scientists may also use it as a reference to find mathematical methods suitable to their research problems. Moreover, the book should be appropriate for self-teaching. It will also be a guide for teachers. Numerous references are included to assist the reader in his search for the pertinent literature. |
| basic math for social scientists: Matrix Algebra Narayanan Krishnan Namboodiri, 1984-07 Conducted under the umbrella of Project Gunrunner, intended to stem the flow of firearms to Mexico, the Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF) ran a series of gun walking sting operations, including Operations Wide Receiver and Operation Fast & Furious. The government allowed licensed gun dealers to sell weapons to illegal straw buyers so that they could continue to track the firearms as they were transferred to higher-level traffickers and key figures in Mexican cartels.Motivated by a sense of patriotic duty, Tucson gun dealer and author Mike Detty alerted the local ATF office when he was first approached by suspected cartel associates. Detty made the commitment and assumed the risks involved to help the feds make their case, often selling guns to these thugs from his home in the dead of night. Originally informed that the investigation would last just weeks, Detty s undercover involvement in Operation Wide Receiver, the precursor to Operation Fast & Furious, which was by far the largest gun walking probe, stretched on for an astonishing and dangerous three years.Though the case took several twists and turns, perhaps the cruelest turn was his betrayal by the very agency he risked everything to help. |
| basic math for social scientists: Learning Basic Mathematics John C. Hunter, Armstrong, Chouteau, 1980 |
| basic math for social scientists: A Mathematical Primer for Social Statistics John Fox, 2021-01-11 A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic language of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a math camp or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods. |
| basic math for social scientists: Visible Learning for Social Studies, Grades K-12 John Hattie, Julie Stern, Douglas Fisher, Nancy Frey, 2020-04-07 Help students move from surface-level learning to the transfer of understanding. How do social studies teachers maximize instruction to ensure students are prepared for an informed civic life? VISIBLE LEARNING® for Social Studies, Grades K-12 shows how the field is more than simply memorizing dates and facts—it encapsulates the skillful ability to conduct investigations, analyze sources, place events in historical context, and synthesize divergent points of view. The Visible Learning framework demonstrates that learning is not an event, but rather a process in which students move from surface-level learning to deep learning, and then onto the transfer of concepts, skills, and strategies. Encouraging learners to explore different facets of society, history, geography, and more, best practices for applying visible learning to social studies curriculum are presented through: · A scaffolded approach, including surface-level learning, deep learning, and transfer of learning · Examples of strategies, lessons, and activities best suited for each level of learning · Planning tools, rubrics, and templates to guide instruction Teachers must understand the impact they have on students and select approaches to maximize that impact. This book will guide you through the process of identifying the right strategy for the right time to successfully move students through surface, deep, and transfer learning. |
| basic math for social scientists: Rethinking Mathematics Eric Gutstein, Bob Peterson, 2005 In this unique collection, more than 30 articles show how to weave social justice issues throughout the mathematics curriculum, as well as how to integrate mathematics into other curricular areas. Rethinking Mathematics offers teaching ideas, lesson plans, and reflections by practitioners and mathematics educators. This is real-world math-math that helps students analyze problems as they gain essential academic skills. This book offers hope and guidance for teachers to enliven and strengthen their math teaching. It will deepen students' understanding of society and help prepare them to be critical, active participants in a democracy. Blending theory and practice, this is the only resource of its kind. |
| basic math for social scientists: How Students Learn National Research Council, Division of Behavioral and Social Sciences and Education, Committee on How People Learn: A Targeted Report for Teachers, 2005-01-28 How Students Learn: Science in the Classroom builds on the discoveries detailed in the best-selling How People Learn. Now these findings are presented in a way that teachers can use immediately, to revitalize their work in the classroom for even greater effectiveness. Organized for utility, the book explores how the principles of learning can be applied in science at three levels: elementary, middle, and high school. Leading educators explain in detail how they developed successful curricula and teaching approaches, presenting strategies that serve as models for curriculum development and classroom instruction. Their recounting of personal teaching experiences lends strength and warmth to this volume. This book discusses how to build straightforward science experiments into true understanding of scientific principles. It also features illustrated suggestions for classroom activities. |
| basic math for social scientists: Chaos Theory in the Social Sciences L. Douglas Kiel, Euel W. Elliott, 1997-09-26 DIVApplications of chaos theory in political science, economics, and sociology /div |
| basic math for social scientists: Mathematics for Social Scientists Jonathan Kropko, 2015-09-09 Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students’ confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students’ reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations. |
| basic math for social scientists: Mathematics for Natural Scientists Lev Kantorovich, 2015-10-08 This book covers a course of mathematics designed primarily for physics and engineering students. It includes all the essential material on mathematical methods, presented in a form accessible to physics students, avoiding precise mathematical jargon and proofs which are comprehensible only to mathematicians. Instead, all proofs are given in a form that is clear and convincing enough for a physicist. Examples, where appropriate, are given from physics contexts. Both solved and unsolved problems are provided in each section of the book. Mathematics for Natural Scientists: Fundamentals and Basics is the first of two volumes. Advanced topics and their applications in physics are covered in the second volume. |
| basic math for social scientists: 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. |
| basic math for social scientists: Intro Math Analysis for Business, Economics, and the Life and Social Sciences, Books a la Carte Edition Ernest F. Haeussler, Jr., Richard S. Paul, Richard J. Wood, 2009-07-01 This classic book continues to provide a foundation for mathematical literacy in business, economics, and the life and social sciences. Covers concepts ranging from introductory equations and functions through curve sketching, integration, and multivariable calculus. Helps readers connect concepts with the world around them through genuine applications, covering such diverse areas as business, economics, biology, medicine, sociology, psychology, ecology, statistics, earth science, and archaeology. Updates exercises, problems, and Mathematical Snapshots throughout. Improves writing style and mathematical derivations without sacrificing the book's signature flavor. For anyone interested in learning more about introductory mathematical analysis. |
| basic math for social scientists: Introduction to Mathematical Sociology Phillip Bonacich, Philip Lu, 2012-04 A comprehensive textbook on the tools of mathematical sociology and their applications Mathematical models and computer simulations of complex social systems have become everyday tools in sociology. Yet until now, students had no up-to-date textbook from which to learn these techniques. Introduction to Mathematical Sociology fills this gap, providing undergraduates with a comprehensive, self-contained primer on the mathematical tools and applications that sociologists use to understand social behavior. Phillip Bonacich and Philip Lu cover all the essential mathematics, including linear algebra, graph theory, set theory, game theory, and probability. They show how to apply these mathematical tools to demography; patterns of power, influence, and friendship in social networks; Markov chains; the evolution and stability of cooperation in human groups; chaotic and complex systems; and more. Introduction to Mathematical Sociology also features numerous exercises throughout, and is accompanied by easy-to-use Mathematica-based computer simulations that students can use to examine the effects of changing parameters on model behavior. Provides an up-to-date and self-contained introduction to mathematical sociology Explains essential mathematical tools and their applications Includes numerous exercises throughout Features easy-to-use computer simulations to help students master concepts |
| basic math for social scientists: The Multivariate Social Scientist Graeme D Hutcheson, Nick Sofroniou, 1999-05-19 Starting from simple hypothesis testing and then moving towards model-building, this valuable book takes readers through the basics of multivariate analysis including: which tests to use on which data; how to run analyses in SPSS for Windows and GLIM4; how to interpret results; and how to report and present the reports appropriately. Using a unified conceptual framework (based around the Generalized Linear Model) the authors explain the commonalities and relationships between methods that include both the analysis of categorical and continuous data. |
| basic math for social scientists: 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. |
| basic math for social scientists: Programming with Python for Social Scientists Phillip D. Brooker, 2020-02-17 As data become ‘big’, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of – and control over – how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including: the fundamentals of why and how to do your own programming in social scientific research, questions of ethics and research design, a clear, easy to follow ‘how-to’ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more. Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis. |
| basic math for social scientists: Beautiful Symmetry Alex Berke, 2020-02-18 A coloring book that invites readers to explore symmetry and the beauty of math visually. Beautiful Symmetry is a coloring book about math, inviting us to engage with mathematical concepts visually through coloring challenges and visual puzzles. We can explore symmetry and the beauty of mathematics playfully, coloring through ideas usually reserved for advanced courses. The book is for children and adults, for math nerds and math avoiders, for educators, students, and coloring enthusiasts. Through illustration, language that is visual, and words that are jargon-free, the book introduces group theory as the mathematical foundation for discussions of symmetry, covering symmetry groups that include the cyclic groups, frieze groups, and wallpaper groups. The illustrations are drawn by algorithms, following the symmetry rules for each given group. The coloring challenges can be completed and fully realized only on the page; solutions are provided. Online, in a complementary digital edition, the illustrations come to life with animated interactions that show the symmetries that generated them. Traditional math curricula focus on arithmetic and the manipulation of numbers, and may make some learners feel that math is not for them. By offering a more visual and tactile approach, this book shows how math can be for everyone. Combining the playful and the pedagogical, Beautiful Symmetry offers both relaxing entertainment for recreational colorers and a resource for math-curious readers, students, and educators. |
| basic math for social scientists: Smarter Charts for Math, Science, and Social Studies Kristine Mraz, Marjorie Martinelli, 2014 Problems with the charts in your math kit? Want to discover the science of content-area charts? Wish you could make pre-fab social studies charts history? Then you're ready for Smarter Charts for Math, Science, and Social Studies! In the original Smarter Charts, Marjorie Martinelli and Kristi Mraz helped you turn classroom literacy charts into teaching powerhouses. Now they show how to turn up the instructional energy on content-area charts, too. No matter what area of the curriculum, clear visuals, simple language, and constant reflection on charts are key to helping children gain independence and agency. You don't have to be a graphic designer or a subject-matter expert. In Smarter Charts for Math, Science, and Social Studies, Marjorie and Kristi share how they learned to make truly effective content-area charts with students. You'll turn complex ideas into kid-friendly visuals, help children internalize content processes, and even increase your instructional time. The more we charted, the less repeating we did and the more teaching was possible. With dozens of examples from the content areas, including full-color photographs, the Chartchums reveal step by step how to create charts that show Routines, Genres and Concepts, Processes, Repertoires of Strategies, and Exemplars. Then their Charts in Action sections show how each type of chart builds engagement and improves independence as it gradually releases responsibility to learners. Don't be content with content-area charts made by someone else for generic students. Turn to Marjorie and Kristi for charts that make learning visible for the students in front of you, no matter what the subject. Check out these videos from the authors! Kristi Mraz and Marjorie Martinelli Show Us the Tools for Smarter Charts Chart tips from the ChartChums: Part 1 Drawing People Chart tips from the ChartChums: Part 2 Icons |
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当然，平台都有局限性，并且有一定的平台费用。 最好的获客方式就是你的个人品牌——当你已经有了非常丰富的项目经验时，和人脉积累时，自然会有人找上你来。
个人4盘位NAS，用什么RAID比较合适，为什么？ - 知乎
两盘位basic：存放电影，下载，电脑备份等非重要数据。 可扩展一盘位usb外接（可以用电脑替代，更理想情况是有第二台nas）：使用套件做最重要的数据定期同步或备份，电影种子，basic …
2025年，鼠标垫推荐、FPS游戏鼠标垫推荐、游戏鼠标垫推荐、办 …
三、无线充电鼠标垫 （1）罗技POWERPLAY无线充电鼠标垫. 罗技的POWERPLAY无线充电鼠标垫是为罗技支持powerplay无线充电技术的鼠标专用的，有一个非常优秀的特点就是可以边使 …
如何origin在一个图中画两条线，比如这种? - 知乎
导入数据到各个列中，全选数据后，点击 Origin 工具栏上的 Plot ——> Basic 2D ——> Line + Symbol 或者 点击 Origin 下边快捷图标 ，如下图所示 Origin 就会自动绘制两条数据线，如下图 …
为什么说以Basic作为入门语言会变成脑残？ - 知乎
Dijkstra说的这个basic是上古时期的basic，参考小霸王上的basic。其中充斥着GOTO，每行必须有行号，行号满了就不能插入，变量命名受限，没有指针和动态内存分配，有很多使其无法胜任 …
base，basic，basis这个三个词怎么区分? - 知乎
Aug 7, 2020 · basic（尤指作为发展的起点）基本的，初步的，如： 6. He doesn't have mastery of the basic skills of reading, writing and communicating. 他还没掌握基本的读写和交流技巧。【 …
excel2021visual basic打开是灰色的怎么办？ - 知乎
如果Excel 2021 中的 Visual Basic 编辑器打开时显示为灰色，可能是由于以下原因之一： 安装问题：确保已正确安装了 Visual Basic for Applications（VBA）组件。 检查 Microsoft Office 安 …
一文了解Transformer全貌（图解Transformer） - 知乎
Jan 21, 2025 · Transformer整体结构（输入两个单词的例子） 为了能够对Transformer的流程有个大致的了解，我们举一个简单的例子，还是以之前的为例，将法语"Je suis etudiant"翻译成英 …
安装plc博途出现automation license manager 问题 怎么搞啊 ? - 知乎
Jun 22, 2021 · 换了好几个安装包都出现这个问题，别人还要我换系统 但是文件太多了 不好换 还有没有其他办法啊
如何合理的检索外文参考文献的出版地和出版商？ - 知乎
我的毕业论文参考文献中有大量的[sl]和[sn]标志,前者是表示出版地未知，后者是表示出版商未知，我需要高…
如何开始 Freelancer 生涯？ - 知乎
当然，平台都有局限性，并且有一定的平台费用。 最好的获客方式就是你的个人品牌——当你已经有了非常丰富的项目经验时，和人脉积累时，自然会有人找上你来。
个人4盘位NAS，用什么RAID比较合适，为什么？ - 知乎
两盘位basic：存放电影，下载，电脑备份等非重要数据。 可扩展一盘位usb外接（可以用电脑替代，更理想情况是有第二台nas）：使用套件做最重要的数据定期同步或备份，电影种子，basic …
2025年，鼠标垫推荐、FPS游戏鼠标垫推荐、游戏鼠标垫推荐、办 …
三、无线充电鼠标垫 （1）罗技POWERPLAY无线充电鼠标垫. 罗技的POWERPLAY无线充电鼠标垫是为罗技支持powerplay无线充电技术的鼠标专用的，有一个非常优秀的特点就是可以边使 …
如何origin在一个图中画两条线，比如这种? - 知乎
导入数据到各个列中，全选数据后，点击 Origin 工具栏上的 Plot ——> Basic 2D ——> Line + Symbol 或者 点击 Origin 下边快捷图标 ，如下图所示 Origin 就会自动绘制两条数据线，如下图 …
