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An Introduction to Cultural Ecology
by Mark Q. Sutton E. N. AndersonThis contemporary introduction to the principles and research base of cultural ecology is the ideal textbook for advanced undergraduate and beginning graduate courses that deal with the intersection of humans and the environment in traditional societies. After introducing the basic principles of cultural anthropology, environmental studies, and human biological adaptations to the environment, the book provides a thorough discussion of the history of, and theoretical basis behind, cultural ecology. The bulk of the book outlines the broad economic strategies used by traditional cultures: hunting/gathering, horticulture, pastoralism, and agriculture. Fully explicated with cases, illustrations, and charts on topics as diverse as salmon ceremonies among Northwest Indians, contemporary Maya agriculture, and the sacred groves in southern China, this book gives a global view of these strategies. An important emphasis in this text is on the nature of contemporary ecological issues, how peoples worldwide adapt to them, and what the Western world can learn from their experiences. A perfect text for courses in anthropology, environmental studies, and sociology.
An Introduction to Culture and Psychology: A Sociocultural Perspective
by Valery ChirkovThe book offers an innovative introduction to culture and psychology, taking a sociocultural perspective to understand the complexities of culture-mind-behaviour interactions.In this book, the author emphasizes the dynamic relationship of the culture and the mind, outlining how organized sociocultural models regulate actions and practices across different domains of people’s lives, such as parenting, education, communication, and acculturation. Each chapter features chapter synopsis, boxed examples, a glossary of key terms, reflective questions, and recommended reading to help students engage further with the material. The book includes a range of cross-cultural case study examples and discussions which offer insights into the connections between culture, human psyche, and behaviour.An Introduction to Culture and Psychology is essential reading for undergraduate students taking culture and psychology courses. It can also be of interest to students and young scholars of psychology, anthropology, sociology, communication, and other related disciplines.
An Introduction to Curriculum Studies (Routledge Library Editions: Curriculum #34)
by Philip H. Taylor Colin M. RichardsOriginally published in 1979 with a second edition in 1985. A basic text for students of education and teachers who are coming to terms for the first time with the nature of the curriculum. It introduces the reader to the professional field that is of concern to all engaged in the practical enterprise of education in a way which provides a ‘feel’ for the preoccupations of the area and a ‘sense’ of its complexities. With annotated further reading included, the book reflects developments in all the major areas in curriculum design and evaluation and in effecting curriculum change, plus research and theory.
An Introduction to Cyber Analysis and Targeting
by Jerry M. CouretasThis book provides a comprehensive view of cyber operations, analysis and targeting, including operational examples viewed through a lens of conceptual models available in current technical and policy literature. Readers will gain a better understanding of how the current cyber environment developed, as well as how to describe it for future defense. The author describes cyber analysis first as a conceptual model, based on well-known operations that span from media to suspected critical infrastructure threats. He then treats the topic as an analytical problem, approached through subject matter interviews, case studies and modeled examples that provide the reader with a framework for the problem, developing metrics and proposing realistic courses of action. Provides first book to offer comprehensive coverage of cyber operations, analysis and targeting;Pulls together the various threads that make up current cyber issues, including information operations to confidentiality, integrity and availability attacks;Uses a graphical, model based, approach to describe as a coherent whole the development of cyber operations policy and leverage frameworks;Provides a method for contextualizing and understanding cyber operations.
An Introduction to Cyber Modeling and Simulation (Wiley Series in Modeling and Simulation #88)
by Jerry M. CouretasIntroduces readers to the field of cyber modeling and simulation and examines current developments in the US and internationally This book provides an overview of cyber modeling and simulation (M&S) developments. Using scenarios, courses of action (COAs), and current M&S and simulation environments, the author presents the overall information assurance process, incorporating the people, policies, processes, and technologies currently available in the field. The author ties up the various threads that currently compose cyber M&S into a coherent view of what is measurable, simulative, and usable in order to evaluate systems for assured operation. An Introduction to Cyber Modeling and Simulation provides the reader with examples of tools and technologies currently available for performing cyber modeling and simulation. It examines how decision-making processes may benefit from M&S in cyber defense. It also examines example emulators, simulators and their potential combination. The book also takes a look at corresponding verification and validation (V&V) processes, which provide the operational community with confidence in knowing that cyber models represent the real world. This book: Explores the role of cyber M&S in decision making Provides a method for contextualizing and understanding cyber risk Shows how concepts such the Risk Management Framework (RMF) leverage multiple processes and policies into a coherent whole Evaluates standards for pure IT operations, "cyber for cyber," and operational/mission cyber evaluations—"cyber for others" Develops a method for estimating both the vulnerability of the system (i.e., time to exploit) and provides an approach for mitigating risk via policy, training, and technology alternatives Uses a model-based approach An Introduction to Cyber Modeling and Simulation is a must read for all technical professionals and students wishing to expand their knowledge of cyber M&S for future professional work.
An Introduction to Cybercultures
by David BellAn Introduction to Cybercultures provides an accessible guide to the major forms, practices and meanings of this rapidly-growing field. From the evolution of hardware and software to the emergence of cyberpunk film and fiction, David Bell introduces readers to the key aspects of cyberculture, including email, the internet, digital imaging technologies, computer games and digital special effects. Each chapter contains `hot links' to key articles in its companion volume, The Cybercultures Reader, suggestions for further reading, and details of relevant websites. Individual chapters examine: · Cybercultures: an introduction · Storying cyberspace · Cultural Studies in cyberspace · Community and cyberculture · Identities in cyberculture · Bodies in cyberculture · Cybersubcultures · Researching cybercultures
An Introduction to Cybernetic Synergy: Improving Decision-Making and Cost Efficiency in Business and Commercial Environments
by Mark RowbothamCybernetics is about having a goal and taking action to achieve that goal. Knowing whether you have reached your goal (or at least are getting closer to it) requires “feedback”, a concept that was made rigorous by cybernetics. The subject of Cybernetic Synergy, although emanating from a socio-economic experiment of economic control by cybernetic means in Chile in the early 1970s, has never been approached as an applied subject in its own right. Indeed, the subject of applied cybernetics has never been addressed as a separate issue, although it has been shown that the overall subject of cybernetics applies to a wide range of disciplines, from biology to business via mathematics and engineering. Cybernetic synergy is the study of relationships and controls of and between corporate entities, on an external basis, and departments within corporate entities, on an internal basis. It concerns the decision-making process, and how decisions can be made based on feedback from any part of the organization being managed. It therefore concerns the issue of input of raw material or information, the output of the transformed information and materials, and the rectification of any issue based on negative feedback related to the productive process. It investigates not only the basic theory of the subject but also its applications in the commercial and business environment, as well as touching on government and administrative issues where shortcomings have emerged owing to a lack of synergy and communication. There are already several books available on the subject to cybernetics, but they are all concerned with mathematical approaches along with very heavy technical texts, most of which are completely alien to the layman or the simple practitioner. Furthermore, other than references to business or economic practice in some books, there has never been a book published purely about the subject of applied cybernetics relating to business practices. The book covers the subjects of management and economic cybernetics, and how the theory of cybernetic control can be used to manage business and government functions, whether small, medium or large. It looks at the history of cybernetics, and how some pioneering cybernetic concepts were used in Chile in the early 1970s to manage the Chilean economy. It uses these same principles, along with later cybernetic models, to show how such concepts can be applied to the present-day economy and business practices. It examines present-day business practices and shows how weaknesses in these systems can be addressed and eliminated by the application of cybernetic practices. The aims of the book are to provide an insight into the subject of management and business cybernetics, using the principle of cybernetic synergy, to resolve intra-corporate issues and create more efficient business practices based on simple command-and-control processes. Essentially, this book provides an in-depth insight into the use of cybernetics in business and administration environments, and would explain how cybernetics is a valuable tool in resolving corporate issues concerning efficiency and overall control. It would give a detailed explanation of the various practices and functions involved in business operations and practices.
An Introduction to Cyberpsychology
by Irene Connolly, Palmer Marion, Barton Hannah and Kirwan GráinneAn Introduction to Cyberpsychology is the first book to provide a student-oriented introduction to this rapidly growing and increasingly studied topic. It is designed to encourage students to critically evaluate the psychology of online interactions, and to develop appropriate research methodologies to complete their own work in this field. The book is comprised of four main sections: An overview of cyberpsychology and online research methodologies Social psychology in an online context The practical applications of cyberpsychology The psychological aspects of other technologies. Each chapter includes: Explanations of key terms and a glossary to facilitate understanding Content summaries to aid student learning Activity boxes, discussion questions and recommended reading to guide further study. Further resources for students and instructors are available on the book’s companion website, including audio and video links, essay questions, a multiple-choice test bank, and PowerPoint lecture slides. Uniquely combining a survey of the field with a focus on the applied areas of psychology, the book is designed to be a core text for undergraduate modules in cyberpsychology and the psychology of the internet, and a primer for students of postgraduate programs in cyberpsychology.
An Introduction to Cyberpsychology (BPS Core Textbooks Series)
by Gráinne Kirwan, Irene Connolly, Hannah Barton, and Marion PalmerAn Introduction to Cyberpsychology provides a comprehensive introduction to this rapidly growing discipline. Fully updated in its second edition, the book encourages students to critically evaluate the psychology of online interactions and to develop appropriate research methodologies to complete their own work in this field.The book examines cyberpsychology and online research methodologies, social psychology in an online context, practical applications of cyberpsychology, and the psychological aspects of other technologies. This new edition has been carefully updated to include additional coverage of: Expanded content relating to major developments in the field and new content on gaming and screentime A new chapter examining the relationship between older adults and technology Cyberpsychology in focus feature boxes in each chapter that examine topics in depth Interviews with professionals working in fields relating to cyberpsychology Each chapter includes key terms and a glossary, content summaries, discussion questions, and recommended reading to guide further study.Supported by extensive online resources for students and instructors, this authoritative book is an essential core text for undergraduate modules in cyberpsychology, and an ideal primer for students of postgraduate programs in cyberpsychology.To view the additional student and instructor resources for this book, please visit bpscoretextbooks.routledge.com
An Introduction to Daoist Philosophies
by Steve CoutinhoSteve Coutinho explores in detail the fundamental concepts of Daoist thought as represented in three early texts: the Laozi, the Zhuangzi, and the Liezi. Readers interested in philosophy yet unfamiliar with Daoism will gain a comprehensive understanding of these works from this analysis, and readers fascinated by ancient China who also wish to grasp its philosophical foundations will appreciate the clarity and depth of Coutinho's explanations.Coutinho writes a volume for all readers, whether or not they have a background in philosophy or Chinese studies. A work of comparative philosophy, this volume also integrates the concepts and methods of contemporary philosophical discourse into a discussion of early Chinese thought. The resulting dialogue relates ancient Chinese thought to contemporary philosophical issues and uses modern Western ideas and approaches to throw new interpretive light on classical texts. Rather than function as historical curiosities, these works act as living philosophies in conversation with contemporary thought and experience. Coutinho respects the multiplicity of Daoist philosophies while also revealing a distinctive philosophical sensibility, and he provides clear explanations of these complex texts without resorting to oversimplification.
An Introduction to Daoist Thought: Action, Language, and Ethics in Zhuangzi
by Eske MøllgaardThis is the first work available in English which addresses Zhuangzi’s thought as a whole. It presents an interpretation of the Zhuangzi, a book in thirty-three chapters that is the most important collection of Daoist texts in early China. The author introduces a complex reading that shows the unity of Zhuangzi’s thought, in particular in his views of action, language, and ethics. By addressing methodological questions that arise in reading Zhuangzi, a hermeneutics is developed which makes understanding Zhuangzi’s religious thought possible. A theoretical contribution to comparative philosophy and the cross-cultural study of religious traditions, the book serves as an introduction to Daoism for graduate students in religion, philosophy, and East Asian Studies.
An Introduction to Data Analysis Using IBM SPSS
by Lokesh JasraiThis textbook elaborates on the basic understanding and application of statistical tests and data analysis using hypothetical datasets and SPSS version 22.0. It presents step-by-step processes and to-the-point interpretation for quick assimilation and comprehension.Data Analysis Using SPSS Begins with the stages of data entry and goes on till editing and data visualization. Takes the readers through descriptive statistics, frequency, univariate, bivariate and regression analysis, cross-tabulation, linear models and non-parametric test procedures. Presents information through dialog boxes and tabular charts, and also incorporates important formulae, calculations and illustrations of sample data for an in-depth understanding of concepts and results. Can be used as a textbook as well as a reference book as it helps to build conceptual understanding, gaining software skills, and communicates data and its insights to accomplish research assignments, research/capstone projects and PhD research work. With comprehensive coverage, this book would be useful to the students, researchers and teachers of the various social sciences disciplines like Psychology, Sociology, Education, Social Work, Agriculture Management and other allied subjects. It would also be an invaluable companion to professionals and data scientists working in the field of analytics.
An Introduction to Data Analysis in R: Hands-on Coding, Data Mining, Visualization and Statistics from Scratch (Use R!)
by Alfonso Zamora Saiz Carlos Quesada González Lluís Hurtado Gil Diego Mondéjar RuizThis textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.
An Introduction to Data Analysis using Aggregation Functions in R
by Simon JamesThis textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background. Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects. This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.
An Introduction to Data Analysis: Quantitative, Qualitative and Mixed Methods
by Tiffany BerginCovering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.
An Introduction to Data Analysis: Quantitative, Qualitative and Mixed Methods
by Tiffany BerginCovering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.
An Introduction to Data Science
by Jeffrey S. Saltz Jeffrey Morgan StantonAn Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio® from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions. The authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the math behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions. Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks.
An Introduction to Data Science
by Jeffrey S. Saltz Jeffrey Morgan StantonAn Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio® from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions. The authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the math behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions. Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks.
An Introduction to Data Science With Python
by Jeffrey S. Saltz Jeffrey Morgan StantonAn Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
An Introduction to Data Science With Python
by Jeffrey S. Saltz Jeffrey Morgan StantonAn Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.
An Introduction to Data-Driven Control Systems
by Ali Khaki-SedighAn Introduction to Data-Driven Control Systems An introduction to the emerging dominant paradigm in control design Model-based approaches to control systems design have long dominated the control systems design methodologies. However, most models require substantial prior or assumed information regarding the plant’s structure and internal dynamics. The data-driven paradigm in control systems design, which has proliferated rapidly in recent decades, requires only observed input-output data from plants, making it more flexible and broadly applicable. An Introduction to Data-Driven Control Systems provides a foundational overview of data-driven control systems methodologies. It presents key concepts and theories in an accessible way, without the need for the complex mathematics typically associated with technical publications in the field, and raises the important issues involved in applying these approaches. The result is a highly readable introduction to what promises to become the dominant control systems design paradigm. Readers will also find: An overview of philosophical-historical issues accompanying the emergence of data-driven control systems Design analysis of several conventional data-driven control systems design methodologies Algorithms and simulation results, with numerous examples, to facilitate the implementation of methods An Introduction to Data-Driven Control Systems is ideal for students and researchers in control theory or any other research area related to plant design and production.
An Introduction to Data: Everything You Need to Know About AI, Big Data and Data Science (Studies in Big Data #50)
by Francesco CoreaThis book reflects the author’s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies.
An Introduction to Decision Theory
by Martin PetersonThis introduction to decision theory offers comprehensive and accessible discussions of decision-making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory, and social choice theory. No mathematical skills are assumed, and all concepts and results are explained in non-technical and intuitive as well as more formal ways. There are over 100 exercises with solutions, and a glossary of key terms and concepts. An emphasis on foundational aspects of normative decision theory (rather than descriptive decision theory) makes the book particularly useful for philosophy students, but it will appeal to readers in a range of disciplines including economics, psychology, political science and computer science.
An Introduction to Decision Theory
by Martin PetersonThis introduction to decision theory offers comprehensive and accessible discussions of decision-making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory, and social choice theory. No mathematical skills are assumed, and all concepts and results are explained in non-technical and intuitive as well as more formal ways. There are over 100 exercises with solutions, and a glossary of key terms and concepts. An emphasis on foundational aspects of normative decision theory (rather than descriptive decision theory) makes the book particularly useful for philosophy students, but it will appeal to readers in a range of disciplines including economics, psychology, political science and computer science.