Probability and statistics

This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives.

Now in its second edition, this book brings multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations.

This book is a detailed introduction to selective maintenance and updates readers on recent advances in this field, emphasizing mathematical formulation and optimization techniques.

This carefully curated volume presents an in-depth, state-of-the-art discussion on many applications of Synthetic Aperture Radar (SAR).

This Festschrift celebrates Teddy Seidenfeld and his seminal contributions to philosophy, statistics, probability, game theory and related areas.

The book describes the theoretical principles of nonstatistical methods of data analysis but without going deep into complex mathematics.

The book describes the theoretical principles of nonstatistical methods of data analysis but without going deep into complex mathematics.

The new edition of this innovative book, R Data Analysis without Programming, prepares the readers to quickly analyze data and interpret statistical results using R.

Companies are scrambling to integrate AI into their systems and operations.

Companies are scrambling to integrate AI into their systems and operations.

This book is designed to be a practical study in infectious disease dynamics.

The main aim of this book is to offer an easy tool to read a scientific article with greater awareness, to understand and evaluate it more thoroughly, and to better plan research.

Generating function (GF) is a mathematical technique to concisely represent a known ordered sequence into a simple continuous algebraic function in dummy variable(s).

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century.

The sixth edition provides expanded Discussion and Comments and References sections at the end of each chapter, creating a spotlight on practical applications of the theory presented in that chapter.

Brain, Decision Making, and Mental Health acknowledges that thinking is not a constant phenomenon but varies considerably across cultures.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with the applications of Excel VBA, Python and R.

This book describes official statistics as a tool to hold up a mirror to society - but also as an instrument for those who can manipulate this mirror.

This book organizes principles and methods of signal processing and machine learning into the framework of coherence.

This concise, easy-to-read pocket guide offers medical trainees, researchers, and clinicians at every level the perfect resource on Evidence Based Medicine (EBM).

This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022.

This book teaches foundations of epidemiological design and statistical methods, as well as including topics applicable to new areas of research.

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes.

This book provides a contemporary treatment of the problems related to anomalous diffusion and anomalous relaxation.

This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s.

This book focuses on analysing the applications of the Shannon Measure of Information (SMI).

Bei allen Erkenntnissen, die im COVID-Prozess erfahren wurden, bleibt eine wesentliche erhalten: "Das Virus bleibt ein ständiger Begleiter".

Through the lens of critical thinking and creative analogy, this book skillfully blends mainstream perspectives with bold, thought-provoking personal insights, offering readers a fresh and engaging perspective on complex topics.

This book provides expository derivations for moments of a family of pseudo distributions, which is an extended family of distributions including the pseudo normal (PN) distributions recently proposed by the author.

This book explores the molecular mechanisms of iron hemostasis in the brain and discusses the cognitive and behavioral implications of iron deficiency.

Developed from the authors' graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes.

Census data is widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions.

Census data is widely used by practitioners to understand demographic change, allocate resources, address inequalities, and make sound business decisions.

This textbook will continue to be the best suitable textbook written specifically for a first course on probability theory and designed for industrial engineering and operations management students.

This textbook will continue to be the best suitable textbook written specifically for a first course on probability theory and designed for industrial engineering and operations management students.

Psychological Statistics: The Basics walks the reader through the core logic of statistical inference and provides a solid grounding in the techniques necessary to understand modern statistical methods in the psychological and behavioral sciences.

Psychological Statistics: The Basics walks the reader through the core logic of statistical inference and provides a solid grounding in the techniques necessary to understand modern statistical methods in the psychological and behavioral sciences.

This book develops an original theory of decision-making based on the concept of plausibility.

This book develops an original theory of decision-making based on the concept of plausibility.

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences.

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks.

Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise.

Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise.

Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks.

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python.

This book discusses the payout phase of the old-age pension saving scheme, the so-called effective premium, and offers detailed actuarial models and analyses of five old-age pension saving products used in practice.

This book provides practical demonstrations of how to carry out definite integrals with Monte Carlo methods using Mathematica.

This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general.