Probability and statistics

Sample surveys is the most important branch of statistics.

The Theory of Probability is a major tool that can be used to explain and understand the various phenomena in different natural, physical and social sciences.

This book provides a basic grounding in the use of probability to model random financial phenomena of uncertainty, and is targeted at an advanced undergraduate and graduate level.

Most modern textbooks on cluster analysis are written from the standpoint of computer science, which give the background, description and implementation of computer algorithms.

This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory.

Two features of Processing Random Data differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques.

This book teaches modern Markov chain Monte Carlo (MC) simulation techniques step by step.

This book contains topics that can be covered in a single-semester course.

Most books on reliability theory are devoted to traditional binary reliability models allowing for only two possible states for a system and its components: perfect functionality and complete failure.

Probability theory is an important part of contemporary mathematics.

This textbook is an introduction to probability theory using measure theory.

This book discusses systematically treatment on the development of stochastic, statistical and state space models of the HIV epidemic and of HIV pathogenesis in HIV-infected individuals, and presents the applications of these models.

Modelling with the Ito integral or stochastic differential equations has become increasingly important in various applied fields, including physics, biology, chemistry and finance.

NewsProfessor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University).

This book covers selected topics in geometry, algebra, calculus and probability theory.

This book concentrates on the topic of evaluation of Jacobians in some specific linear as well as nonlinear matrix transformations, in the real and complex cases, which are widely applied in the statistical, physical, engineering, biological and social sciences.

This book presents a rigorous exposition of probability theory for a variety of applications.

This volume is representative of the work of Chinese probabilitists on probability theory and its applications in physics.

This book is an introductory text on geostatistics which treats spatially distributed random data and can be applied to areas like ore reserve assessment, pollution problems, forestry applications and water resource problems.

This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner.

Most introductory textbooks on stochastic processes which cover standard topics such as Poisson process, Brownian motion, renewal theory and random walks deal inadequately with their applications.

This textbook provides an introduction to statistics for computer users or computer science undergraduates.

In this book, an integrated introduction to statistical inference is provided from a frequentist likelihood-based viewpoint.

The personal computer has made statistical analysis easier and cheaper.

The 1952 Nobel physics laureate Felix Bloch (1905-83) was one of the titans of twentieth-century physics.

This invaluable book consists of two parts.

This book has been designed for senior engineering, mathematics and systems science students.

This textbook consists of three parts: basic concepts of statistics, advanced statistical methods, and design and analysis for medical research.

This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics, engineering statistics and medical statistics courses.

The first edition of this classic book has become the authoritative reference for physicists desiring to master the finer points of statistical data analysis.

Explanation of the basic concepts and methods of statistics requires a reasonably good mathematical background, at least at a first-year-level knowledge of calculus.

This book belongs to the subject of control and systems theory.

The book presents the fundamental concepts from asymptotic statistical inference theory, elaborating on some basic large sample optimality properties of estimators and some test procedures.

This book introduces empirical methods for analyzing energy markets.

This book provides analytic tools to describe local and global behavior of solutions to Ito-stochastic differential equations with non-degenerate Sobolev diffusion coefficients and locally integrable drift.

This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time.

This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC)  without assuming advanced knowledge of mathematics and programming.

This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy.

This book analyzes the development of medical big data projects in Japan.

As a comprehensive textbook in survey sampling, this book discusses the inadequacies of classic, designed-based inferential procedures and provides alternative approaches in the form of model formulations, model-design-based procedures of analysis, inference and interpretation.

In commemoration of the bicentennial of the birth of the "e;lady who gave the rose diagram to us"e;, this special contributed book pays a statistical tribute to Florence Nightingale.

This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion: basic latent structure models in a framework of generalized linear models, exploratory latent class analysis, latent class analysis with ordered latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path analysis with latent class models.

This book presents a study of the COVID-19 pandemic using computational social scientific analysis that draws from, and employs, statistics and simulations.

This book provides a thorough conversation on the underpinnings of Covid-19 spread modelling by using stochastics nonlocal differential and integral operators with singular and non-singular kernels.

This book belongs to the subject of control and systems theory.

This book discusses recent theoretical developments in agglomerative hierarchical clustering.

This book proposes a bank risk aggregation framework based on financial statements.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than relying on knowledge or experience.

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than relying on knowledge or experience.