Probability and statistics

In a fast moving world, businesses need to keep up with data analysis and pattern spotting to identify future opportunities.

Focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis in various disciplines.

This text covers both multiple linear regression and some experimental design models.

A substantial enhancement of the only text devoted entirely to the negative binomial model and its many variations.

Bohmian Mechanics was formulated in 1952 by David Bohm as a complete theory of quantum phenomena based on a particle picture.

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19.

This book constitutes the refereed proceedings of the Fourth International Symposium on Algorithmic Game Theory, SAGT 2011, held in Amalfi, Italy, in October 2011.

With the primary goal of expanding access to spatial data science tools, this book offers dozens of minimal or low-code functions and tutorials designed to ease the implementation of fully reproducible Spatial Socio-Econometric Modeling (SSEM) analyses.

This textbook shows how to bring theoretical concepts from finance and econometrics to the data.

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

This volume contains the proceedings from two closely related workshops: Computational Diffusion MRI (CDMRI'13) and Mathematical Methods from Brain Connectivity (MMBC'13), held under the auspices of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, which took place in Nagoya, Japan, September 2013.

A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets.

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting.

Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook.

Indicators are more and more applied to describe and analyze complex systems.

This book serves as a hands-on guide to the "e;acs"e; R package for demographers, planners, and other researchers who work with American Community Survey (ACS) data.

Actuarial loss models are statistical models used by insurance companies to estimate the frequency and severity of future losses, set premiums, and reserve funds to cover potential claims.

This book is the first in the literature to present the state of the art and some interesting and relevant applications of the Fuzzy Analytic Hierarchy Process (FAHP).

This is the first comprehensive book on information geometry, written by the founder of the field.

?

This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program.

The 2nd International Workshop on Statistical Methods in Video Processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on Computer Vision.

This book discusses statistical methods and their innovative applications in precision health.

This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management.

This book provides an introductory treatment of time series econometrics, a subject that is of key importance to both students and practitioners of economics.

Excel has become an important and nearly ubiquitous classroom and office resource for students and practitioners who are faced with solving statistical problems on an everyday basis.

Nowadays bioinformaticians and geneticists are faced with myriad high-throughput data usually presenting the characteristics of uncertainty, high dimensionality and large complexity.

"e;We live in the age of data.

This book shows that research contributions from different fields-finance, economics, computer sciences, and physics-can provide useful insights into key issues in financial and cryptocurrency markets.

This volume presents the proceedings of the 18th International Probabilistic Workshop (IPW), which was held in Guimaraes, Portugal in May 2021.

This book describes how reliability can be embedded into the product development using a design methodology that uses parametric accelerated lifecycle testing (ALT) .

After unification large amounts of money were spent to retrain the East Germany labour force in order to ease the transition to the new market economy.

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.

This volume introduces the theoretical ideas in probability and statistics by means of examples.

Since the publication of the first edition of this book, the area of mathematical finance has grown rapidly, with financial analysts using more sophisticated mathematical concepts, such as stochastic integration, to describe the behavior of markets and to derive computing methods.

Hoy en dia vivimos en un mundo repleto de información, es decir, de datos, y no cabe duda que para interpretarlos correctamente es fundamental el conocimiento de la Estadística, que podría definirse como el arte de obtener conclusiones a partir de datos.

Developed from the author's course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs).

Winner of the 2017 AERA Division D Significant Contribution to Educational Measurement and Research Methodology Award!

This book is concerned with the relations between graphs, error-correcting codes and designs.

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories.

Probability and Mathematical Statistics: An Introduction provides a well-balanced first introduction to probability theory and mathematical statistics.

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity.

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data.

Of related interest.

This collection of papers is dedicated to David Kendall, the topics will interest postgraduate and research mathematicians.