This textbook provides a comprehensive, thorough and up-to-date treatment of topics of mathematics that an engineer and scientist would need, at the basic levels that contents of engineering and sciences are built by. For this purpose, natural readers would be junior and senior undergraduate students, who normally have the content of this book under different names on their degree plans. Also, engineers and scientists will benefit from this book since the book is a comprehensive volume for such audiences. This book is written in a way that it balances both theory and practical applications of topics from linear algebra, matrix theory, calculus of multivariable, theory of complex variables, several transforms, ordinary and partial differential equations, difference equations, optimization, probability, statistics, theory of reliability and finally, applications from variety of areas of sciences and engineering.

Studies on queuing models and their publication in professional journals and textbooks have been sparse over the past eleven decades. Collections of some of these studies have appeared either as single volumes or just chapters of single volumes and/or monographs. This book is an attempt to present some queuing models, especially those applicable in business and industry, in a style between a monograph and a textbook. Also the need of researchers and practitioners for a handbook-type text and the current lack of it explain the need for a book of this kind. Most of the basic terminologies and concepts that appear throughout the text are introduced in a systematic way in the first two chapters; nevertheless, previous exposition to a first course in probability and statistics is advised for later chapters. The principal audiences for the book are senior undergraduates (first three chapters) and graduate students (all six chapters). It is also a hope that the volume will appeal to a wider audience of specialists and researchers in mathematical science, engineering, physics, business and economics.

Studies on queueing models and their publication in professional journals and textbooks have been sparse over the past eleven decades. Collections of some of these studies have appeared either as single volumes or just chapters of single volumes and/or monographs. This book is an attempt to present some queuing models, especially those applicable in business and industry, in a style between a monograph and a textbook. Also the need of researchers and practitioners for a handbook-type text and the current lack of it explain the need for a book of this kind. Most of the basic terminologies and concepts that appear throughout the text are introduced in a systematic way in the first two chapters; nevertheless, previous exposition to a first course in probability and statistics is advised for later chapters.

Topics in advanced mathematics for engineers, probability and statistics typically span three subject areas, are addressed in three separate textbooks and taught in three different courses in as many as three semesters. Due to this arrangement, students taking these courses have had to shelf some important and fundamental engineering courses until much later than is necessary. This practice has generally ignored some striking relations that exist between the seemingly separate areas of statistical concepts, such as moments and estimation of Poisson distribution parameters. On one hand, these concepts commonly appear in stochastic processes - for instance, in measures on effectiveness in queuing models. On the other hand, they can also be viewed as applied probability in engineering disciplines - mechanical, chemical, and electrical, as well as in engineering technology. There is obviously, an urgent need for a textbook that recognizes the corresponding relationships between the various areas and a matching cohesive course that will see through to their fundamental engineering courses as early as possible. This book is designed to achieve just that. Its seven chapters, while retaining their individual integrity, flow from selected topics in advanced mathematics such as complex analysis and wavelets to probability, statistics and stochastic processes.