Sandsynlighedsregning og statistik

Dieses Buch führt in die angewandte Statistik für Agrarwissenschaften ein und unterstützt bei der Forschung in der Pflanzen- und Tierproduktion und im Feldversuchswesen. Es nutzt ausgiebig das frei verfügbare Programmpaket R: Über das gesamte Buch hinweg werden im Rahmen umfangreicher Beispiele passende R-Programmcodes angegeben und erläutert. Die Codes können mit eigenen Daten kombiniert und so zur Planung und Auswertung eigener Versuche verwendet werden. So können etwa Wachstumsfunktionen angepasst, Varianzanalysen berechnet oder optimale Versuchspläne und minimale Stichprobenumfänge gefunden werden und vieles mehr. Eine Installationsbeschreibung für R wird ebenfalls zur Verfügung gestellt. Zahlreiche Übungsaufgaben mit Lösungen ergänzen das Buch, so dass es als Lehr- und Nachschlagewerk nutzbar ist.Besonders hervorzuheben ist, dass auch balancierte unvollständige Blockanlagen (BUB) erläutert werden und erstmalig eine vollständige Liste kleinster (mit möglichst geringer Anzahl von Blocks) BUB für bis zu v = 25 Behandlungen und Blockgrößen ¿ v/2 im Netz zur Verfügung gestellt wird. Für Sortenversuche sind die BUB allerdings oft nicht nutzbar, weil sie zu viele Wiederholungen erfordern. Dafür haben sich ¿verallgemeinerte Gitter¿ oder alpha-Anlagen bewährt, die ebenfalls behandelt werden.

Introduction to Stochastic Level Crossing Techniques describes stochastic models using the System Point Level Crossing method. This involves deriving probability density functions or cumulative probability distribution functions of key random variables, applying simple level-crossing limit theorems.

The fields of Artificial Intelligence and Machine Learning have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between Mathematics and AI/ML and provides an overview of the current research streams.

The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.

This book includes sections on foundational principles and on putting those principles into practice. Connections between these individual skills are emphasized such that the reader can appreciate how the skills build upon each other leading to a whole that is greater than the sum of its parts.

This book is intended for anyone who is considering a career in statistics or a related field, or those at any point in their career with sufficient work time remaining such that investing in additional learning could be beneficial. As such, the book would be suitable for anyone pursing an MS or PhD in statistics or those already working in statistics. The book focuses on the non-statistical aspects of being a statistician that are crucial for success. These factors include 1) productivity and prioritization, 2) innovation and creativity, 3) communication, 4) critical thinking and decisions under uncertainty, 5) influence and leadership, 6) working relationships, and 7) career planning and continued learning. Each of these chapters includes sections on foundational principles and a section on putting those principles into practice. Connections between these individual skills are emphasized such that the reader can appreciate how the skills build upon each other leading to a whole that is greater than the sum of its parts. By including the individual perspectives from other experts on the fundamental principles and their application, readers will have a well-rounded view on how to build upon and fully leverage their technical skills in statistics. The primary audience for the book is large and diverse. It will be useful for self-study by virtually any statistician, but could also be used as a text in a graduate program that includes a course on careers and career development.Key Features:Takes principles proven to be useful in other settings and applies them to statisticians and statistical settings.FocusedConciseAccessible to all levels, from grad students to mid-later career statisticians.

This book introduces the fundamentals of the technology satisfaction model (TSM), supporting readers in applying the Rasch model and Structural Equation Modelling (SEM) - a multivariate technique - to higher education (HE) research. User satisfaction is traditionally measured along a single dimension.

This book examines the latest developments in AI-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications.

This book was written to provide guidance for those who need to apply statistical methods for practical use. While the book provides detailed guidance on the use of Minitab for calculation, simply entering data into a software program is not sufficient to reliably gain knowledge from data. The software will provide an answer, but the answer may be wrong if the sample was not taken properly, the data was unsuitable for the statistical test that was performed, or the wrong test was selected. It is also possible that the answer will be correct, but misinterpreted. This book provides both guidance in applying the statistical methods described as well as instructions for performing calculations without a statistical software program such as Minitab.One of the authors is a professional statistician who spent nearly 13 years working at Minitab and the other is an experienced and certified Lean Six Sigma Master Black Belt. Together, they strive to present the knowledge of a statistician in a format that can be easily understood and applied by non-statisticians facing real-world problems.Their guidance is provided with the goal of making data analysis accessible and practical. Rather than focusing on theoretical concepts, the book delivers only the information that is critical to success for the practitioner. It is a thorough guide for those who have not yet been exposed to the value of statistics, as well as a reliable reference for those who have been introduced to statistics but are not yet confident in their abilities.Supplemental files available! If you are an instructor who would like to conduct training with this book, please visit this "https://asqassets.widencollective.com/portals/sybdffda/(H1550)AppliedStatisticsManualAGuidetoImprovingandSustainingQualitywithMinitab" access: Course descriptions for one or two semester university courses Chapter descriptions for standalone sessions A data file containing data sets used in the book

The book covers various topics related to inventory management, including different inventory models, techniques for optimizing inventory management, and strategies for improving inventory control. Some of the topics covered include the economic order quantity (EOQ) model, just-in-time (JIT) inventory system, vendor-managed inventory (VMI), and collaborative planning, forecasting, and replenishment (CPFR). The chat also discusses the importance of inventory management in terms of reducing costs, improving efficiency, and enhancing customer service. Overall, the book provides a comprehensive overview of various aspects of inventory management and highlights the importance of effective inventory management in achieving business success.

¿This book presents a critical overview of statistical fiber bundle models, including existing models and potential new ones. The authors focus on both the physical and statistical aspects of a specific load-sharing example: the breakdown for circuits of capacitors and related dielectrics. In addition, they investigate some areas of open research.This book is designed for graduate students and researchers in statistics, materials science, engineering, physics, and related fields, as well as practitioners and technicians in materials science and mechanical engineering.

Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book's dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented.The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference.In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book.The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.

This book introduces the advances in synchromodal logistics and provides a framework to classify various optimisation problems in this field. It explores the application of this framework to solve a broad range of problems, such as problems with and without a central decision-maker, problems with and without full information, deterministic problems, problems coping with uncertainty, optimisation of a full network design problem. It covers theoretical constructs, such as discrete optimisation, robust optimisation, optimisation under uncertainty, multi-objective optimisation and agent based equilibrium models. Moreover, practical elaborated use cases are presented to deepen understanding. The book gives both researchers and practitioners a good overview of the field of synchromodal optimisation problems and offers the reader practical methods for modelling and problem-solving.

Statistik für Mediziner - leicht gemacht.Studien zu planen und durchzuführen gehört für viele Ärzte zum Berufsalltag. Doch worauf kommt es beim Studiendesign und der Interpretation der Ergebnisse an? Ganz klar - auf Kenntnisse in Statistik!Auch die 3. überarbeitete Auflage des etablierten Werkes behandelt die für die Medizin wichtigsten statistischen Verfahren auf leicht verständliche Weise. Die Autoren sprechen die Sprache der Ärzte und haben die Themen nach ihrer Praxisrelevanz ausgewählt. Alles Wissenswerte rund um Zufall und Wahrscheinlichkeit wird auf den "Puls der Klinik" zugeschnitten, erklärt und anhand von Beispielen und 174 Übungsaufgaben vertieft.Ein idealer Begleiter für Ärzte, Gesundheitswissenschaftler und alle im Medizinbereich Tätigen, die sich Statistikkenntnisse aneignen oder sie auffrischen wollen.

Bayesian Analysis of Etiological Factors for Gallbladder Disease by Richa Srivastava explores the use of Bayesian statistical methods to identify risk factors associated with gallbladder disease. The book focuses on the analysis of several demographic, lifestyle, and clinical factors that contribute to the development of the disease.The book provides a detailed analysis of the factors that influence the probability of developing gallbladder disease, including age, gender, smoking, alcohol consumption, and body mass index. The author uses Bayesian methods to analyze the data and develop models that accurately predict the likelihood of developing the disease based on these factors.The book also discusses the limitations of traditional statistical methods and highlights the advantages of Bayesian analysis in identifying complex risk factors associated with diseases. This comprehensive analysis of the etiological factors for gallbladder disease is a valuable resource for researchers, clinicians, and public health professionals.Overall, Bayesian Analysis of Etiological Factors for Gallbladder Disease provides a novel approach to understanding the risk factors associated with the disease and provides insights that can inform prevention and treatment strategies.

This book is about silly research studies and how they can both be illustrative of the research process and funny (with the focus on funny). This book has a two-fold purpose. The first is to show that research studies, even with the best of intention, can be flawed to the point of being ridiculous. The second is to show the reader how they can develop their own study, using available software and techniques to develop a new hobby. Have you ever imagined what it was like to perform a research study? Well, here is your chance. Read the book and maybe you can laugh and learn at the same time.

< div="">This book introduces undergraduate students of engineering and science to applied mathematics essential to the study of many problems. Topics are differential equations, power series, Laplace transforms, matrices and determinants, vector analysis, partial differential equations, complex variables, and numerical methods. Approximately, 160 examples and 1000 homework problems aid students in their study. This book presents mathematical topics using derivations rather than theorems and proofs. This textbook is uniquely qualified to apply mathematics to physical applications (spring-mass systems, electrical circuits, conduction, diffusion, etc.), in a manner that is efficient and understandable. This book is written to support a mathematics course after differential equations, to permit several topics to be covered in one semester, and to make the material comprehensible to undergraduates. An Instructor Solutions Manual, and also a Student Solutions Manual that provides solutions to select problems, is available.^

This book addresses the problem of multi-agent systems, considering that it can be interpreted as a generalized multi-synchronization problem. From manufacturing tasks, through encryption and communication algorithms, to high-precision experiments, the simultaneous cooperation between multiple systems or agents is essential to successfully carrying out different modern activities, both in academy and industry. For example, the coordination of multiple assembler robots in manufacturing lines. These agents need to synchronize.The first two chapters of the book describe the synchronization of dynamical systems, paying special attention to the synchronization of non-identical systems. Following, the third chapter presents an interesting application of the synchronization phenomenon for state estimation. Subsequently, the authors fully address the multi-agent problem interpreted as multi-synchronization. The final chapters introduce the reader to a more complex problem, the synchronization of systems governed by partial differential equations, both of integer and fractional order.The book aimed at graduates, postgraduate students and researchers closely related to the area of automatic control. Previous knowledge of linear algebra, classical and fractional calculus is requested, as well as some fundamental notions of graph theory.