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  • Measure, Integration & Real Analysis
    Measure, Integration & Real Analysis

    This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis.Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results.Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics. Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration.Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach.Lebesgue integration links into results such as the Lebesgue Differentiation Theorem.The development of products of abstract measures leads to Lebesgue measure on Rn. Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem.An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures.Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform.The final chapter offers a taste of probability. Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics.A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysisthat is freely available online.For errata and updates, visit https://measure.axler.net/

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  • Principles of Analysis : Measure, Integration, Functional Analysis, and Applications
    Principles of Analysis : Measure, Integration, Functional Analysis, and Applications

    Principles of Analysis: Measure, Integration, Functional Analysis, and Applications prepares readers for advanced courses in analysis, probability, harmonic analysis, and applied mathematics at the doctoral level.The book also helps them prepare for qualifying exams in real analysis.It is designed so that the reader or instructor may select topics suitable to their needs.The author presents the text in a clear and straightforward manner for the readers’ benefit.At the same time, the text is a thorough and rigorous examination of the essentials of measure, integration and functional analysis. The book includes a wide variety of detailed topics and serves as a valuable reference and as an efficient and streamlined examination of advanced real analysis.The text is divided into four distinct sections: Part I develops the general theory of Lebesgue integration; Part II is organized as a course in functional analysis; Part III discusses various advanced topics, building on material covered in the previous parts; Part IV includes two appendices with proofs of the change of the variable theorem and a joint continuity theorem.Additionally, the theory of metric spaces and of general topological spaces are covered in detail in a preliminary chapter . Features: Contains direct and concise proofs with attention to detail Features a substantial variety of interesting and nontrivial examples Includes nearly 700 exercises ranging from routine to challenging with hints for the more difficult exercises Provides an eclectic set of special topics and applications About the Author:Hugo D.Junghenn is a professor of mathematics at The George Washington University.He has published numerous journal articles and is the author of several books, including Option Valuation: A First Course in Financial Mathematics and A Course in Real Analysis.His research interests include functional analysis, semigroups, and probability.

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  • Principles of Analysis : Measure, Integration, Functional Analysis, and Applications
    Principles of Analysis : Measure, Integration, Functional Analysis, and Applications

    Principles of Analysis: Measure, Integration, Functional Analysis, and Applications prepares readers for advanced courses in analysis, probability, harmonic analysis, and applied mathematics at the doctoral level.The book also helps them prepare for qualifying exams in real analysis.It is designed so that the reader or instructor may select topics suitable to their needs.The author presents the text in a clear and straightforward manner for the readers’ benefit.At the same time, the text is a thorough and rigorous examination of the essentials of measure, integration and functional analysis. The book includes a wide variety of detailed topics and serves as a valuable reference and as an efficient and streamlined examination of advanced real analysis.The text is divided into four distinct sections: Part I develops the general theory of Lebesgue integration; Part II is organized as a course in functional analysis; Part III discusses various advanced topics, building on material covered in the previous parts; Part IV includes two appendices with proofs of the change of the variable theorem and a joint continuity theorem.Additionally, the theory of metric spaces and of general topological spaces are covered in detail in a preliminary chapter . Features: Contains direct and concise proofs with attention to detail Features a substantial variety of interesting and nontrivial examples Includes nearly 700 exercises ranging from routine to challenging with hints for the more difficult exercises Provides an eclectic set of special topics and applicationsAbout the Author:Hugo D.Junghenn is a professor of mathematics at The George Washington University.He has published numerous journal articles and is the author of several books, including Option Valuation: A First Course in Financial Mathematics and A Course in Real Analysis.His research interests include functional analysis, semigroups, and probability.

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  • Computational Analysis of Communication
    Computational Analysis of Communication

    Provides clear guidance on leveraging computational techniques to answer social science questions In disciplines such as political science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing.Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more.Computational Analysis of Communication teaches social science students and practitioners how computational methods can be used in a broad range of applications, providing discipline-relevant examples, clear explanations, and practical guidance. Assuming little or no background in data science or computer linguistics, this accessible textbook teaches readers how to use state-of-the art computational methods to perform data-driven analyses of social science issues.A cross-disciplinary team of authors—with expertise in both the social sciences and computer science—explains how to gather and clean data, manage textual, audio-visual, and network data, conduct statistical and quantitative analysis, and interpret, summarize, and visualize the results.Offered in a unique hybrid format that integrates print, ebook, and open-access online viewing, this innovative resource: Covers the essential skills for social sciences courses on big data, data visualization, text analysis, predictive analytics, and othersIntegrates theory, methods, and tools to provide unified approach to the subjectIncludes sample code in Python and links to actual research questions and cases from social science and communication studiesDiscusses ethical and normative issues relevant to privacy, data ownership, and reproducible social scienceDeveloped in partnership with the International Communication Association and by the editors of Computational Communication Research Computational Analysis of Communication is an invaluable textbook and reference for students taking computational methods courses in social sciences, and for professional social scientists looking to incorporate computational methods into their work.

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  • What is a communication analysis?

    A communication analysis is the process of examining and evaluating the effectiveness of communication within a specific context or organization. This can involve studying the methods, channels, and content of communication to identify strengths, weaknesses, and areas for improvement. Communication analysis can also involve assessing the impact of communication on relationships, decision-making, and overall organizational performance. The goal of communication analysis is to gain insights into how communication functions and to make recommendations for enhancing its effectiveness.

  • How do I write a communication analysis?

    To write a communication analysis, start by selecting a communication piece to analyze, such as a speech, advertisement, or conversation. Next, identify the purpose, audience, and context of the communication. Then, analyze the key elements of the communication, such as the message, tone, language, and nonverbal cues. Finally, evaluate the effectiveness of the communication in achieving its intended goals and consider any potential improvements or alternative strategies that could enhance the communication.

  • How can one focus on communication in an analysis?

    To focus on communication in an analysis, one can start by clearly defining the purpose and audience of the communication. It is important to identify key messages and ensure they are conveyed effectively. Paying attention to the tone, language, and medium of communication can also help in delivering the message clearly. Additionally, actively listening to feedback and being open to adjusting the communication strategy can further enhance the effectiveness of the analysis.

  • What is the topic of the communication analysis exam?

    The topic of the communication analysis exam is to evaluate and analyze various forms of communication, such as verbal, nonverbal, written, and visual communication. Students are expected to demonstrate their understanding of communication theories, principles, and concepts, as well as their ability to critically analyze different communication strategies and their effectiveness in various contexts. The exam may also cover topics related to interpersonal communication, organizational communication, mass communication, and the impact of technology on communication.

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  • Social Network Analysis
    Social Network Analysis

    Incorporating the most important and cutting-edge developments in the field, this bestselling text introduces newcomers to the key theories and techniques of social network analysis and guides more experienced analysts in their own research. New to This Edition:A chapter on data collection, covering a crucial phase of the research processFully updated examples reiterate the continued importance of social network analysis in an increasingly interconnected worldDetailed ‘Further Reading’ sections help you explore the wider literaturePractical exercises including real-world examples of social networks enable you to apply your learningExpanded and brought right up-to-date, this classic text remains the indispensable guide to social network analysis for students, lecturers and researchers throughout the social sciences.

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  • Social Network Analysis
    Social Network Analysis

    David Knoke and Song Yang's Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis.The authors convey key material while at the same time minimizing technical complexities.The examples are simple: sets of 5 or 6 entities such as individuals, positions in a hierarchy, political offices, and nation-states, and the relations between them include friendship, communication, supervision, donations, and trade.The new edition reflects developments and changes in practice over the past decade.The authors also describe important recent developments in network analysis, especially in the fifth chapter.Exponential random graph models (ERGMs) are a prime example: when the second edition was published, P* models were the recommended approach for this, but they have been replaced by ERGMs. Finally, throughout the volume, the authors comment on the challenges and opportunities offered by internet and social media data.

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  • Inferential Network Analysis
    Inferential Network Analysis

    This unique textbook provides an introduction to statistical inference with network data.The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised.Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research.From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions.The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.

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  • Africa’s Economic Partnership with China : An Holistic Analysis
    Africa’s Economic Partnership with China : An Holistic Analysis

    This book examines how increasing Africa-China relations in the fields of trade, development finance and investment have impacted productive capacities and structural economic transformation in sub-Saharan Africa (SSA).The book argues that statistical and empirical evidence shows that China’s influence has not substantially altered the fundamentals in Africa, and instead outlines a framework of policy conclusions and recommendations to help achieve transformational growth and development.Despite increased Chinese investments in transport, energy, communications, and manufacturing, sub-Saharan Africa is yet to see tangible economic and development benefits according to the multidimensional Productive Capacities Index (PCI).External trade is dogged by the same problems as during the colonial era, with primary commodities dominating exports to China, and industrial or manufacturing products dominating imports, thereby leaving the region exposed to external economic shocks.The book considers whether there are lessons to be learned from the experience of Asian countries such as Vietnam, proposing pragmatic, coordinated, non-ideological, and non-confrontational policy approaches to development.This book will be of interest to researchers, policymakers, advisors, academics, and practitioners with an interest in development in Africa, and China’s increasing role in the continent.

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  • How does network analysis work in electrical engineering?

    Network analysis in electrical engineering involves studying and analyzing the behavior of electrical circuits. This analysis helps in understanding how different components in a circuit interact with each other and how signals flow through the network. By using techniques such as Kirchhoff's laws, nodal analysis, and mesh analysis, engineers can determine important parameters like voltage, current, power, and impedance in a circuit. This information is crucial for designing, optimizing, and troubleshooting electrical systems. Overall, network analysis plays a key role in ensuring the efficient and reliable operation of electrical networks.

  • How do I interpret a negative interaction term in moderation analysis?

    In moderation analysis, a negative interaction term suggests that the relationship between the independent variable and the dependent variable is weaker when the moderator variable is present. This means that the moderator variable diminishes or weakens the effect of the independent variable on the dependent variable. It indicates that the relationship between the independent and dependent variables is not as strong when the moderator variable is at higher levels. Overall, a negative interaction term suggests that the moderator variable has a dampening effect on the relationship between the independent and dependent variables.

  • Which good short story is suitable for a communication analysis exercise?

    A good short story suitable for a communication analysis exercise is "Hills Like White Elephants" by Ernest Hemingway. This story is rich in dialogue and relies heavily on non-verbal communication between the characters to convey the underlying tension and conflict. Analyzing the characters' interactions, tone, and body language in this story can provide valuable insights into the complexities of communication and the power dynamics at play in relationships.

  • How can one write the focus on communication in an analysis?

    One can write the focus on communication in an analysis by examining the various communication channels used, such as verbal, nonverbal, written, and digital communication. It is important to analyze the effectiveness of the communication in conveying the intended message and achieving the desired outcome. Additionally, one can explore the barriers to effective communication, such as language barriers, cultural differences, and misunderstandings, and how they impact the overall communication process. Finally, it is crucial to consider the context and audience of the communication to understand how it influences the message and its reception.

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