- Table View
- List View
Research Methods and Statistics in Psychology
by Hugh CoolicanResearch Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project, giving advice on planning and conducting studies, analysing data and writing up reports, both quantitative and qualitative. It incorporates diversity and includes a large section on cross-cultural psychology methods and issues. The book continues its long tradition of integrating qualitative issues into methods chapters as well as providing two chapters dedicated to qualitative methods. It provides clear coverage of experimental, interviewing and observational methods; psychological testing; and statistical procedures which include nominal-level tests, ordinal and interval two-condition tests, simple and multi-factorial ANOVA designs, correlation, multiple regression, log linear analysis, factor analysis and, new with this edition, logistic regression. It features detailed and illustrated SPSS instructions for all these and other procedures, eliminating the need for an extra SPSS textbook. New edition features include: • Logistic regression. • Greater detail of online research methods. • Expanded coverage of report writing guidelines. • Concepts illustrated with up-to-date published research examples. • Instructor and Student Resource website signposted throughout the book to improve student usability. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. This book is extended and enhanced by a fully updated and refreshed Instructor and Student Resource website, which includes: • A collection of interactive multiple-choice questions with detailed feedback, providing the opportunity to test understanding at different levels. • Practical exercises that give students the opportunity to put their learning into practice. • Links to further reading and sources to expand knowledge. • Test banks for each chapter to save instructors time. Access the website at: www.routledge.com/cw/coolican.
Research Methods and Statistics in Psychology
by Hugh CoolicanResearch Methods and Statistics in Psychology provides students with the most readable and comprehensive survey of research methods, statistical concepts and procedures in psychology today. Assuming no prior knowledge, this bestselling text takes you through every stage of your research project, giving advice on planning and conducting studies, analysing data and writing up reports, both quantitative and qualitative. It incorporates diversity and includes a large section on cross-cultural psychology methods and issues. The book continues its long tradition of integrating qualitative issues into methods chapters as well as providing two chapters dedicated to qualitative methods. It provides clear coverage of experimental, interviewing and observational methods; psychological testing; and statistical procedures which include nominal-level tests, ordinal and interval two-condition tests, simple and multi-factorial ANOVA designs, correlation, multiple regression, log linear analysis, factor analysis and, new with this edition, logistic regression. It features detailed and illustrated SPSS instructions for all these and other procedures, eliminating the need for an extra SPSS textbook. New edition features include: • Logistic regression. • Greater detail of online research methods. • Expanded coverage of report writing guidelines. • Concepts illustrated with up-to-date published research examples. • Instructor and Student Resource website signposted throughout the book to improve student usability. Each chapter contains a glossary, key terms and newly integrated exercises, ensuring that key concepts are understood. This book is extended and enhanced by a fully updated and refreshed Instructor and Student Resource website, which includes: • A collection of interactive multiple-choice questions with detailed feedback, providing the opportunity to test understanding at different levels. • Practical exercises that give students the opportunity to put their learning into practice. • Links to further reading and sources to expand knowledge. • Test banks for each chapter to save instructors time. Access the website at: www.routledge.com/cw/coolican.
Research Software Engineering: A Guide to the Open Source Ecosystem (Chapman & Hall/CRC Data Science Series)
by Matthias BannertResearch Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Features overview: breakdown of complex data science software stacks into core components applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software reader guidance: different entry points and rich references to deepen the understanding of selected aspects
Research Software Engineering: A Guide to the Open Source Ecosystem (Chapman & Hall/CRC Data Science Series)
by Matthias BannertResearch Software Engineering: A Guide to the Open Source Ecosystem strives to give a big-picture overview and an understanding of the opportunities of programming as an approach to analytics and statistics. The book argues that a solid "programming" skill level is not only well within reach for many but also worth pursuing for researchers and business analysts. The ability to write a program leverages field-specific expertise and fosters interdisciplinary collaboration as source code continues to become an important communication channel. Given the pace of the development in data science, many senior researchers and mentors, alongside non-computer science curricula lack a basic software engineering component. This book fills the gap by providing a dedicated programming-with-data resource to both academic scholars and practitioners.Key Features overview: breakdown of complex data science software stacks into core components applied: source code of figures, tables and examples available and reproducible solely with license cost-free, open source software reader guidance: different entry points and rich references to deepen the understanding of selected aspects
Responsible Use of AI in Military Systems (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Jan Maarten SchraagenArtificial Intelligence (AI) is widely used in society today. The (mis)use of biased data sets in machine learning applications is well‑known, resulting in discrimination and exclusion of citizens. Another example is the use of non‑transparent algorithms that can’t explain themselves to users, resulting in the AI not being trusted and therefore not being used when it might be beneficial to use it.Responsible Use of AI in Military Systems lays out what is required to develop and use AI in military systems in a responsible manner. Current developments in the emerging field of Responsible AI as applied to military systems in general (not merely weapons systems) are discussed. The book takes a broad and transdisciplinary scope by including contributions from the fields of philosophy, law, human factors, AI, systems engineering, and policy development.Divided into five sections, Section I covers various practical models and approaches to implementing military AI responsibly; Section II focuses on liability and accountability of individuals and states; Section III deals with human control in human‑AI military teams; Section IV addresses policy aspects such as multilateral security negotiations; and Section V focuses on ‘autonomy’ and ‘meaningful human control’ in weapons systems.Key Features: Takes a broad transdisciplinary approach to responsible AI Examines military systems in the broad sense of the word Focuses on the practical development and use of responsible AI Presents a coherent set of chapters, as all authors spent two days discussing each other’s work This book provides the reader with a broad overview of all relevant aspects involved with the responsible development, deployment and use of AI in military systems. It stresses both the advantages of AI as well as the potential downsides of including AI in military systems.
Responsible Use of AI in Military Systems (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Jan Maarten SchraagenArtificial Intelligence (AI) is widely used in society today. The (mis)use of biased data sets in machine learning applications is well‑known, resulting in discrimination and exclusion of citizens. Another example is the use of non‑transparent algorithms that can’t explain themselves to users, resulting in the AI not being trusted and therefore not being used when it might be beneficial to use it.Responsible Use of AI in Military Systems lays out what is required to develop and use AI in military systems in a responsible manner. Current developments in the emerging field of Responsible AI as applied to military systems in general (not merely weapons systems) are discussed. The book takes a broad and transdisciplinary scope by including contributions from the fields of philosophy, law, human factors, AI, systems engineering, and policy development.Divided into five sections, Section I covers various practical models and approaches to implementing military AI responsibly; Section II focuses on liability and accountability of individuals and states; Section III deals with human control in human‑AI military teams; Section IV addresses policy aspects such as multilateral security negotiations; and Section V focuses on ‘autonomy’ and ‘meaningful human control’ in weapons systems.Key Features: Takes a broad transdisciplinary approach to responsible AI Examines military systems in the broad sense of the word Focuses on the practical development and use of responsible AI Presents a coherent set of chapters, as all authors spent two days discussing each other’s work This book provides the reader with a broad overview of all relevant aspects involved with the responsible development, deployment and use of AI in military systems. It stresses both the advantages of AI as well as the potential downsides of including AI in military systems.
Robust and Adaptive Control: With Aerospace Applications (Advanced Textbooks in Control and Signal Processing)
by Eugene Lavretsky Kevin A. WiseRobust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems.The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems. Features of the second edition include:sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation;OBLTR applications to aerospace systems;case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms;realistic examples and simulation data illustrating key featuresof the methods described; andproblem solutions for instructors and MATLAB® code provided electronically.The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors’ extensive professional experience with The Boeing Company. The systems covered are challenging—often open-loop unstable with uncertainties in their dynamics—and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer.Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained.Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value.
Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization
by Maosheng Zheng Jie YuThis book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment. It aims to provide a new idea and novel way to robust design and assessment of product and production and relevant problems. Robust design and assessment of product and production is attractive to both customer and producer since the stability and insensitivity of a product’s quality to uncontrollable factors reflect its value. Taguchi method has been used to conduct robust design and assessment of product and production for half a century, but its rationality is criticized by statisticians due to its casting of both mean value of a response and its dispersion into one index, which doesn’t characterize the issue of simultaneous optimization of above two independent sub-responses sufficiently for robust design, so an appropriate approach is needed. The preference or role of a response in the evaluation is indicated by using preferable probability as the unique index. Thus, the rational approach for robust design and assessment of product and production is formulated by means of probabilistic multi-objective optimization, which reveals the simultaneous optimization of both mean value of a response and its dispersion in manner of joint probability. Besides, defuzzification and fuzzification measurements are involved as preliminary approaches for robust assessment, the latter provides miraculous treatment for the 'target the best' case flexibly.
Robust Machine Learning: Distributed Methods for Safe AI (Machine Learning: Foundations, Methodologies, and Applications)
by Rachid Guerraoui Nirupam Gupta Rafael PinotToday, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed machine learning scheme to be robust to these threats, and how to build provably robust machine learning algorithms. Studying the robustness of machine learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed machine learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe machine learning schemes. In addition to introducing the problem of robustness in modern machine learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. Moreover, the book provides a foundation for future research in this area.
SATs Like a Ninja: Key facts and revision tips to supercharge your SATs
by Andrew JenningsPRAISE FOR BOOKS IN THE LIKE A NINJA SERIES'Super engaging and accessible' PIERS TORDAY'An imaginative and affordable resource' CLASS READS'Jam-packed with top-class tips you won't want to miss' MC GrammarFrom Andrew Jennings, the bestselling author @VocabularyNinja, SATs Like a Ninja is the must-have pocketbook packed with practical advice on how to boost your revision practice and tackle KS2 SATs like a pro.When SATs loom, panic can set in. Have you practised enough prefixes? Can you remember how to calculate a percentage? What was the difference between a colon and a semi-colon, again? There's so much to remember, so many different techniques and tips to grasp – it can be overwhelming for parents, never mind the children! With SATs Like a Ninja, you have everything you need at your fingertips to supercharge your SATs practice. This comprehensive mini guide to Key Stage 2 SATs contains everything a pupil needs to meet the demands of the KS2 National Curriculum assessments. The book is divided into three sections with advice, key concepts and fail-safe strategies throughout. The maths section covers key maths facts, arithmetic and tips to tackle reasoning and word problems. The reading section offers reading strategies, advice, as well as mini texts and associated worked example questions. Finally, the spelling, punctuation and grammar (SPaG) section tackles the trickiest spelling rules, explains those fiddly fronted adverbials and, amongst other things, explores the difference between there, they're and their.For more must-have Ninja books by Andrew Jennings (@VocabularyNinja), check out Vocabulary Ninja, Maths Like a Ninja, Write Like a Ninja, Spell Like a Ninja, SATs Like a Ninja and Comprehension Ninja.
Scaling Up: How Data Curation Can Help Address Key Issues in Qualitative Data Reuse and Big Social Research (Synthesis Lectures on Information Concepts, Retrieval, and Services)
by Sara MannheimerThis book explores the connections between qualitative data reuse, big social research, and data curation. A review of existing literature identifies the key issues of context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. Through interviews of qualitative researchers, big social researchers, and data curators, the author further examines each key issue and produces new insights about how domain differences affect each community of practice’s viewpoints, different strategies that researchers and curators use to ensure responsible practice, and different perspectives on data curation. The book suggests that encouraging connections between qualitative researchers, big social researchers, and data curators can support responsible scaling up of social research, thus enhancing discoveries in social and behavioral science.
Scattering Amplitudes in Quantum Field Theory (Lecture Notes in Physics #1021)
by Simon Badger Johannes Henn Jan Christoph Plefka Simone ZoiaThis open access book bridges a gap between introductory Quantum Field Theory (QFT) courses and state-of-the-art research in scattering amplitudes. It covers the path from basic definitions of QFT to amplitudes, which are relevant for processes in the Standard Model of particle physics. The book begins with a concise yet self-contained introduction to QFT, including perturbative quantum gravity. It then presents modern methods for calculating scattering amplitudes, focusing on tree-level amplitudes, loop-level integrands and loop integration techniques. These methods help to reveal intriguing relations between gauge and gravity amplitudes and are of increasing importance for obtaining high-precision predictions for collider experiments, such as those at the Large Hadron Collider, as well as for foundational mathematical physics studies in QFT, including recent applications to gravitational wave physics.These course-tested lecture notes include numerous exercises with solutions. Requiring only minimal knowledge of QFT, they are well-suited for MSc and PhD students as a preparation for research projects in theoretical particle physics. They can be used as a one-semester graduate level course, or as a self-study guide for researchers interested in fundamental aspects of quantum field theory.
Science Interrupted: Rethinking Research Practice with Bureaucracy, Agroforestry, and Ethnography (Expertise: Cultures and Technologies of Knowledge)
by Timothy G. McLellanScience Interrupted examines how scientists in China pursue environmental sustainability within the constraints of domestic and international bureaucracies. Timothy G. McLellan offers a theoretical framework for analyzing the formal procedural work of Chinese bureaucracy—work that is overlooked when China scholars restrict their gaze to the informal and interpersonal channels through which bureaucracy is often navigated. Homing in on an agroforestry research organization in southwest China, the author takes the experiences of the organization's staff in navigating diverse international funding regimes and authoritarian state institutions as entry points for understanding the pervasiveness of bureaucracy in contemporary science. He asks: What if we take the tools, sensibilities, and practices of bureaucracies seriously not only as objects of critique but as resources for re-thinking scientific practice? Extending a mode of anthropological research in which ethnography serves as source of theory as well as source of data, Science Interrupted thinks with, and not only against, bureaucracy. McLellan shows that ethnographic engagement with bureaucracy enables us to imagine more democratic and more collaborative modes of scientific practice.
Sentiment Analysis and its Application in Educational Data Mining (SpringerBriefs in Applied Sciences and Technology)
by Soni SwetaThe book delves into the fundamental concepts of sentiment analysis, its techniques, and its practical applications in the context of educational data. The book begins by introducing the concept of sentiment analysis and its relevance in educational settings. It provides a thorough overview of the various techniques used for sentiment analysis, including natural language processing, machine learning, and deep learning algorithms. The subsequent chapters explore applications of sentiment analysis in educational data mining across multiple domains. The book illustrates how sentiment analysis can be employed to analyze student feedback and sentiment patterns, enabling educators to gain valuable insights into student engagement, motivation, and satisfaction. It also examines how sentiment analysis can be used to identify and address students' emotional states, such as stress, boredom, or confusion, leading to more personalized and effective interventions. Furthermore, the book explores the integration of sentiment analysis with other educational data mining techniques, such as clustering, classification, and predictive modeling. It showcases real-world case studies and examples that demonstrate how sentiment analysis can be combined with these approaches to improve educational decision-making, curriculum design, and adaptive learning systems.
Session-Based Recommender Systems Using Deep Learning
by Reza Ravanmehr Rezvan MohamadrezaeiThis book focuses on the widespread use of deep neural networks and their various techniques in session-based recommender systems (SBRS). It presents the success of using deep learning techniques in many SBRS applications from different perspectives. For this purpose, the concepts and fundamentals of SBRS are fully elaborated, and different deep learning techniques focusing on the development of SBRS are studied. The book is well-modularized, and each chapter can be read in a stand-alone manner based on individual interests and needs. In the first chapter of the book, definitions and concepts related to SBRS are reviewed, and a taxonomy of different SBRS approaches is presented, where the characteristics and applications of each class are discussed separately. The second chapter starts with the basic concepts of deep learning and the characteristics of each model. Then, each deep learning model, along with its architecture and mathematical foundations, is introduced. Next, chapter 3 analyses different approaches of deep discriminative models in session-based recommender systems. In the fourth chapter, session-based recommender systems that benefit from deep generative neural networks are discussed. Subsequently, chapter 5 discusses session-based recommender systems using advanced/hybrid deep learning models. Eventually, chapter 6 reviews different learning-to-rank methods focusing on information retrieval and recommender system domains. Finally, the results of the investigations and findings from the research review conducted throughout the book are presented in a conclusive summary. This book aims at researchers who intend to use deep learning models to solve the challenges related to SBRS. The target audience includes researchers entering the field, graduate students specializing in recommender systems, web data mining, information retrieval, or machine/deep learning, and advanced industry developers working on recommender systems.
Seven Fundamental Concepts in Spacetime Physics (SpringerBriefs in Physics)
by Vesselin PetkovThe book presents seven fundamental concepts in spacetime physics mostly by following Hermann Minkowski’s revolutionary ideas summarized in his 1908 lecture "Space and Time." These concepts are: spacetime, inertial and accelerated motion in spacetime physics, the origin and nature of inertia in spacetime physics, relativistic mass, gravitation, gravitational waves, and black holes. They have been selected because they appear to be causing most misconceptions and confusion in spacetime physics. This second edition has been revised to include additional clarifications, more detailed elaboration of the arguments and also new material published in the interim.
A Short Introduction to Mathematical Concepts in Physics
by Jim NapolitanoMathematics is the language of physics and yet, mathematics is an enormous subject. This textbook provides an accessible and concise introduction to mathematical physics for undergraduate students taking a one semester course. It assumes the reader has studied a year of introductory physics and three semesters of basic calculus, including some vector calculus, but no formal training in differential equations or matrix algebra. It equips readers with the skills and foundational knowledge they need for courses that follow in classical mechanics, electromagnetism, quantum mechanics, and thermal physics. This book exposes students early on to the kinds of mathematical manipulations they will need in upper-level courses in physics. It can also serve as a useful reference for their further studies. Key features: Accompanied by homework problems and a solutions manual for instructors, available upon qualifying course adoption Bridges the gap between calculus and physics, explaining fundamental mathematics (differentiation, integration, infinite series) in physical terms Explores quick extensions into mathematics useful in physics, not typically taught in math courses, including the Gamma Function, hyperbolic functions, Gaussian integrals, Legendre polynomials, functions of a complex variable, and probability distribution functions
A Short Introduction to Mathematical Concepts in Physics
by Jim NapolitanoMathematics is the language of physics and yet, mathematics is an enormous subject. This textbook provides an accessible and concise introduction to mathematical physics for undergraduate students taking a one semester course. It assumes the reader has studied a year of introductory physics and three semesters of basic calculus, including some vector calculus, but no formal training in differential equations or matrix algebra. It equips readers with the skills and foundational knowledge they need for courses that follow in classical mechanics, electromagnetism, quantum mechanics, and thermal physics. This book exposes students early on to the kinds of mathematical manipulations they will need in upper-level courses in physics. It can also serve as a useful reference for their further studies. Key features: Accompanied by homework problems and a solutions manual for instructors, available upon qualifying course adoption Bridges the gap between calculus and physics, explaining fundamental mathematics (differentiation, integration, infinite series) in physical terms Explores quick extensions into mathematics useful in physics, not typically taught in math courses, including the Gamma Function, hyperbolic functions, Gaussian integrals, Legendre polynomials, functions of a complex variable, and probability distribution functions
SIAM International Meshing Roundtable 2023 (Lecture Notes In Computational Science And Engineering Ser. #147)
by Eloi Ruiz-Gironés Rubén Sevilla David Moxey
Simulation and Statistics with Excel: An Introduction to Business Students
by Luis Fernando IbarraThe use of simulation techniques has increased in importance in recent history, and simulation activities are an important resource for advanced preparation for the organization and execution of events. When formal mathematics is not enough, simulation may be the only option capable of approximating solutions. Simulation and Statistics with Excel: An Introduction to Business Students offers a non-rigorous and practical tour of the simulation procedure on computers, using a versatile and accessible resource, the Microsoft Excel spreadsheet. This book covers the concepts essential to understanding the basic principles and approaches of statistical simulation, allowing for the study of complex systems. Aimed at students in business and operational research beginning to use simulation as an instrument for understanding existing or proposed processes, this book will lay solid foundations in understanding simulation experimentation.Key Features: Provides a basis to understand the approaches and principles of simulator experiments. Uses a universal and easily accessible resource. Introduces simple examples to teach the fundamentals of simulation.
Simulation and Statistics with Excel: An Introduction to Business Students
by Luis Fernando IbarraThe use of simulation techniques has increased in importance in recent history, and simulation activities are an important resource for advanced preparation for the organization and execution of events. When formal mathematics is not enough, simulation may be the only option capable of approximating solutions. Simulation and Statistics with Excel: An Introduction to Business Students offers a non-rigorous and practical tour of the simulation procedure on computers, using a versatile and accessible resource, the Microsoft Excel spreadsheet. This book covers the concepts essential to understanding the basic principles and approaches of statistical simulation, allowing for the study of complex systems. Aimed at students in business and operational research beginning to use simulation as an instrument for understanding existing or proposed processes, this book will lay solid foundations in understanding simulation experimentation.Key Features: Provides a basis to understand the approaches and principles of simulator experiments. Uses a universal and easily accessible resource. Introduces simple examples to teach the fundamentals of simulation.
Smart Card Research and Advanced Applications: 22nd International Conference, CARDIS 2023, Amsterdam, The Netherlands, November 14–16, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14530)
by Shivam Bhasin Thomas RocheThis book constitutes the proceedings of the 22nd International Conference on Smart Card Research and Advanced Applications, CARDIS 2023, held in Amsterdam, The Netherlands, during November 14–16, 2023.The 13 full papers presented in this volume were carefully reviewed and selected from 28 submissions. They were organized in topical sections as follows: fault attacks; side-channel analysis; smartcards & efficient Implementations; and side-channel & neural networks.
Soccer Analytics: An Introduction Using R (Chapman & Hall/CRC Data Science Series)
by Clive BeggsSports analytics is on the rise, with top soccer clubs, bookmakers, and broadcasters all employing statisticians and data scientists to gain an edge over their competitors.Many popular books have been written exploring the mathematics of soccer. However, few supply details on how soccer data can be analysed in real-life. The book addresses this issue via a practical route one approach designed to show readers how to successfully tackle a range of soccer related problems using the easy-to-learn computer language R. Through a series of easy-to-follow examples, the book explains how R can be used to: Download and edit soccer data Produce graphics and statistics Predict match outcomes and final league positions Formulate betting strategies Rank teams Construct passing networks Assess match play Soccer Analytics: An Introduction Using R is a comprehensive introduction to soccer analytics aimed at all those interested in analysing soccer data, be they fans, gamblers, coaches, sports scientists, or data scientists and statisticians wishing to pursue a career in professional soccer. It aims to equip the reader with the knowledge and skills required to confidently analyse soccer data using R, all in a few easy lessons.
Soccer Analytics: An Introduction Using R (Chapman & Hall/CRC Data Science Series)
by Clive BeggsSports analytics is on the rise, with top soccer clubs, bookmakers, and broadcasters all employing statisticians and data scientists to gain an edge over their competitors.Many popular books have been written exploring the mathematics of soccer. However, few supply details on how soccer data can be analysed in real-life. The book addresses this issue via a practical route one approach designed to show readers how to successfully tackle a range of soccer related problems using the easy-to-learn computer language R. Through a series of easy-to-follow examples, the book explains how R can be used to: Download and edit soccer data Produce graphics and statistics Predict match outcomes and final league positions Formulate betting strategies Rank teams Construct passing networks Assess match play Soccer Analytics: An Introduction Using R is a comprehensive introduction to soccer analytics aimed at all those interested in analysing soccer data, be they fans, gamblers, coaches, sports scientists, or data scientists and statisticians wishing to pursue a career in professional soccer. It aims to equip the reader with the knowledge and skills required to confidently analyse soccer data using R, all in a few easy lessons.
Social Research Methods: Qualitative, Quantitative and Mixed Methods Approaches
by Sigmund GronmoFraming research as the process of asking and answering questions, this book demonstrates how to identify good research questions and how to structure and explore them successfully. Whether you are just beginning your research journey or are a seasoned traveller, it helps you: • Decide what you want to achieve with your research • Know what options you have to explore your goals • Navigate the nuances of different research approaches • Understand the decisions of other researchers • Choose what path best suits your project. Through real-life examples demonstrating different types of research, the book introduces qualitative, quantitative, and mixed methods approaches so you can compare different methods at every stage of the research process, from initial idea and design to data collection and analysis. This new edition includes new chapters on collecting and analysing mixed methods data, and additional content on qualitative data analysis. New examples reflect the cultural and global diversity of social research, and extra visual aids and summaries support understanding of key research concepts and stages. The book is accompanied by an online teaching guide, including videos, additional case studies, annotated articles, and critical thinking exercises.