Probability and statistics

Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook.

Roussas introduces readers with no prior knowledge in probability or statistics, to a thinking process to guide them toward the best solution to a posed question or situation.

This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques.

The Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that "e;Students must demonstrate a knowledge of the application of statistics to engineering problems.

A Course in Mathematical Statistics, Second Edition, contains enough material for a year-long course in probability and statistics for advanced undergraduate or first-year graduate students, or it can be used independently for a one-semester (or even one-quarter) course in probability alone.

This book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems.

Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course.

Probability and Statistics is a calculus-based treatment of probability concurrent with and integrated with statistics.

Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS.

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression.

Introduction to Probability and Statistics for Engineers and Scientists, Third Edition, provides an introduction to applied probability and statistics for engineering or science majors .

Mental Chronometry (MC) comprises a variety of techniques for measuring the speed with which the brain processes information.

This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.

Introduction to Probability Models, Ninth Edition, is the primary text for a first undergraduate course in applied probability.

Biostatistics, Second Edition, is a user-friendly guide on biostatistics, which focuses on the proper use and interpretation of statistical methods.

Mixing up various disciplines frequently produces something that are profound and far-reaching.

Mental Chronometry (MC) comprises a variety of techniques for measuring the speed with which the brain processes information.

Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining.

The aim of this book is to report on the progress realized in probability theory in the field of dynamic random walks and to present applications in computer science, mathematical physics and finance.

This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view.

Handbook of Statistics_29B contains the most comprehensive account of sample surveys theory and practice to date.

Provides a coherent and comprehensive account of the theory and practice of real-time human disease outbreak detection, explicitly recognizing the revolution in practices of infection control and public health surveillance.

Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining.

This book is an engaging and insightful exploration of cause-and-effect relationships in clinical research.

This book is an engaging and insightful exploration of cause-and-effect relationships in clinical research.

Dynamic programming is a powerful technique for modeling problems requiring sequential decisions in macroeconomics and finance.

Das Gehirn: Das komplexeste Werkzeug des Universums - eine Gebrauchsanweisung von Hirnforscher und Bestseller-Autor Dr.