Probability and statistics

Data Science in Practice is the ideal introduction to data science.

Se ha dedicado en este texto, mucha reflexion a la seleccion, organizacion y presentacion de la materia, pensando en su exposicion en el aula de clase; pero no se ha intentado ofrecer un libro a la medida de ningun programa ni exactamente ajustado a un calendario.

"e;This is an important book on an important topic.

This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science.

Un libro imprescindible para conocer las últimas teorías psicológicas sobre cómo funciona el pensamiento (y cómo mejorarlo).

In competitive manufacturing industries, organizations embrace product development as a continuous investment strategy since both market share and profit margin stand to benefit.

Baseball is not the only sport to use "e;moneyball.

Baseball is not the only sport to use "e;moneyball.

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine.

This book provides the first consideration of quantum principles in legal decision making.

This book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science.

This book provides the first consideration of quantum principles in legal decision making.

This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions.

This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions.

This textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata.

This book focuses on research in linear algebra, statistics, matrices, graphs and their applications.

Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time.

Patents and other intellectual property (IP) rights are increasingly part of cross-border trade in their own rights.

Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time.

This book provides an introduction to computer-based methods for the analysis of genomic data.

Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "e;tools"e; that make it mostly self-contained.

This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R.

This unique book offers a unified approach to the modeling of rational decision-making under conditions of uncertainty and strategic and competitive interactions among agents.

Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "e;tools"e; that make it mostly self-contained.

This book presents a critical review of the empirical literature that studies the efficiency of the forward and futures markets for foreign exchange.

This book extends the local central limit theorem to Markov chains whose state spaces and transition probabilities are allowed to change in time.

This textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata.

This book presents a critical review of the empirical literature that studies the efficiency of the forward and futures markets for foreign exchange.

Urban Freight Analytics examines the key concepts associated with the development and application of decision support tools for evaluating and implementing city logistics solutions.

This book focuses on research in linear algebra, statistics, matrices, graphs and their applications.

El objetivo de este libro es poner a disposición del público académico propuestas de aula surgidas en este nicho de perfeccionamiento, de manera que permita a otros académicos afrontar con mayor seguridad y rigurosidad la enseñanza de la estadística y las probabilidades.

I began this book with the express purpose of making it the definitive comparison of Secretariat and Man o' War.

Introduction to Stochastic Level Crossing Techniques describes stochastic models and their analysis using the System Point Level Crossing method (abbreviated SPLC or LC).

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine.

No detailed description available for "e;Bayesian Analysis with Python"e;.

In this book, various numerical methods are discussed in a comprehensive way.

Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.

Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.

Business Statistics: A Decision-Making Approach, 11th Edition, is an introductory text for students who do not necessarily have an extensive mathematics background but who need to understand how statistical tools and techniques are applied in business decision making.

In recent years, there has been a growing emphasis on making statistical methods and analytics accessible to health data science researchers and students.

Hierarchical Modeling and Analysis for Spatial Data, Third Edition is the latest edition of this popular and authoritative text on Bayesian modeling and inference for spatial and spatial-temporal data.

AP Teachers' #1 Choice!

Civil and environmental engineers need an understanding of mathematical statistics and probability theory to deal with the variability that affects engineers' structures, soil pressures, river flows and the like.

The progress of science and technology has placed Queueing Theory among the most popular disciplines in applied mathematics, operations research, and engineering.