Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition introduces the fundamentals of probability, statistics, reliability, and risk methods to engineers and scientists for the purposes of data and uncertainty analysis and modeling in support of decision making.
The third edition of this bestselling text presents probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. This provides a measure of continuity and shows the broad use of simulation as a computational tool to inform decision making processes. This edition also features expanded discussions of the analysis of variance, including single- and two-factor analyses, and a thorough treatment of Monte Carlo simulation. The authors not only clearly establish the limitations, advantages, and disadvantages of each method, but also show that data analysis is a continuum rather than the isolated application of different methods.
Like its predecessors, this book continues to serve its purpose well as both a textbook and a reference. Ultimately, readers will find the content of great value in problem solving and decision making, particularly in practical applications.
The text addresses modeling systems where change has affected data that will be used to calibrate and test models of the system. The use of actual hydrologic data will help you learn how to handle the vagaries of real-world hydrologic-change data. All four elements of the modeling process are discussed: conceptualization, formulation, calibration, and verification. Although the book is oriented towards the statistical aspects of modeling, a strong background in statistics is not required. The statistical and modeling methods discussed here will be of value to all disciplines involved in modeling change. With approximately 100 illustrations, Modeling Hydrologic Change will equip you with an understanding with which to perform the proper analyses and modeling of the complex processes that occur across various disciplines.
Fundamentals of Civil Engineering: An Introduction to the ASCE Body of Knowledge addresses this shortfall and helps budding engineers develop the knowledge, skills, and attitudes suggested and implied by the BOK2. Written as a resource for all of the non-technical outcomes not specifically covered in the BOK2, it details fundamental aspects of fourteen outcomes addressed in the second edition of the ASCE Body of Knowledge and encourages a broader perspective and understanding of the role of civil engineers in society as well as the reciprocal influence between civil engineering and social evolution.
With discussion questions and group activities at the end of each chapter, topics covered include humanities and social sciences, experimentation, sustainability, contemporary issues and historical perspectives, risk and uncertainty, communication, public policy, globalization, leadership and teamwork, and professional and ethical responsibilities.
Suitable for both current and former students in pursuit of further breadth and depth of knowledge and professional maturity, this primer promotes introspection, self-evaluation, and self-learning. It details those attitudes that are essential to the achievement of personal and professional success and advancement to positions of leadership, and encourages an appreciation of the human values that are fundamental to professional practice.
Each chapter contains many computational examples, as well as a section on applications that contain additional engineering examples. Each chapter also includes a set of exercise problems.
The problems are designed to meet the needs of instructors in assigning homework and to help students with practicing the fundamental concepts. Although the book was developed with emphasis on engineering and technological problems, the numerical methods can also be used to solve problems in other fields of science.