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Probability, Statistics, and Reliability for Engineers and Scientists, Second Edition

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I teach this material myself and I don't feel the authors met there objectives of a practical, useful introduction to the topics of probability, statistics, and reliability. This book would be difficult to follow outside of a classroom, or without a good background in the course material already.

The introduction begins with a short essay on education and types of ignorance. I found the discussion quite interesting, and then the introduction jumps to the topic of simulation??? This strangle development flow is present throughout the book.

I often liked the beginning of sections, while not liking the development of details latter in the section / chapter. In many cases the details are at a high or advanced level with no transition or gradual ramping up from the introduction. So much material is covered that very few sections have complete coverage. Details are often missing, that is, more than this text will be required to solve common probability, statistics, and reliability problems.

I did find many of the examples interesting, and learned a few new things, again, because I already possessed a good background in the material. Each chapter also ends with interesting suggested computer simulation assignments.

In preparing this book, we strove to achieve the following educational objectives: (1) introducing probability, statistics, and reliability methods to engineering students and practicing engineers, (2) emphasizing the practical use of these methods, and (3) establishing the limitations, advantages, and disadvantages of the methods. Although, the book was developed with emphasis on engineering and technological problems, the methods can also be used to solve problems in other fields of sciences.

Problems that are commonly encountered by engineers require decision making under conditions of uncertainty. The uncertainty can be in the definition of a problem, the available information, the alternative solution methodologies and their results, and the random nature of the solution outcomes. Studies show that in the future engineers will need to solve more complex design problems with decisions made under conditions of limited resources, thus necessitating increased reliance on the proper treatment of uncertainty. Therefore, this book is intended to better prepare future engineers, as well as assist practicing engineers, in understanding the fundamentals of probability, statistics, and reliability methods, especially their applications, limitations, and potentials.

STRUCTURE, FORMAT, AND MAIN FEATURES

We have developed this book with a dual use in mind, as both a self-learning guidebook and as a required textbook for a course. In either case, the text has been designed to achieve important educational objectives.

The nine chapters of the book cover of the following subjects: (1) an introduction to the text that covers uncertainty types, decision analysis, and Taylor series expansion; (2) graphical analysis of data, and the computation of important characteristics of sample measurements and basic statistical characteristics; (3) the fundamentals of probability; (4) the joint behavior of random variables and the probabilistic characteristics of functions of random variables; (5) statistical analyses that include parameter estimation, hypothesis testing, confidence-interval estimation, sample-size determination, and probability-model selection; (6) curve fitting or model development based on data using regression analysis; (7) a formal presentation of Monte Carlo simulation; (8) reliability, risk, and decision analysis; and (9) the use of Bayesian methods in engineering. The book was designed for an introductory course in probability, statistics, and reliability with emphasis on applications. In developing the book, a set of educational outcomes as detailed in Chapter 1 motivated the structure and content of this text. Ultimately, serious readers will find the content of the book to be very useful in engineering problem solving and decision making. One of the most difficult to grasp aspects of probability and statistics is the concept of sampling variation. In engineering practice, an engineer typically has only one sample of data. It is important to recognize that the statistical results would be somewhat different if he or she had collected a different sample, even if that sample were equally likely to have occurred. Simulation is a means of demonstrating the sample-to-sample, or sampling, variation that can be expected. For this reason, we have incorporated a section on simulation at the end of each chapter (Chapters 1 to 6). Performing some simulations is one way of generating a better appreciation for sampling variation that is inherent in statistical problems presented in Chapters 1 to 6. Omitting the sections on simulation does not diminish a reader's understanding of the other sections or chapters. In each chapter of the book, computational examples are given in the individual sections of the chapter, with more detailed engineering applications given in a concluding section. Also, each chapter includes a set of exercise problems that cover the materials of the chapter. The problems were carefully designed to meet the needs of instructors in assigning homework and the readers in practicing the fundamental concepts. The book can be covered in one or two semesters depending the level of a course or the time allocated for topics covered in the book. The chapter sequence can be followed as a recommended sequence. However, if needed, instructors can choose a subset of the chapters for courses that do not permit a complete coverage of all chapters or a coverage that cannot follow the presented order. After completing Chapters 1, 2, and 3, the readers will have sufficient background to follow and understand the materials in the following tracks of chapters: Chapter 4; Chapters 5 and 6; Chapters 7 and 8; and Chapter 9 according to the indicated sequence.

This is a great qualitative text written from a civil and environmental background. As a civil engineer taking a statistics course that was taught from a mechanical and industrial viewpoint, this book presented text and exapmles that came more naturally to me. Some of the qualitative aspects of the book could use improvement, and may make it difficult for use as a primary text book.

This book is mainly targeted for technical professionals such as scientists and engineers. It is well structured each chapter begins with table of contents of its own which I personally like because it adds to clarity of the material and one can easily locate the relevant topic easily within a chapter without having to waste time. Furthermore, it introduces new topic with theory and relatively good explanation of the equations which are followed by good examples. There are lots of graphs and tables which is great because it aids visual learner like myself and the majority of us are visual learners.
There is an additional feature included in this book that one does not find in engineering books and that is to emphasis the application of the theory to real world projects. This is supplemented by the introduction of projects that continue throughout the book to aid students learn the content. This book can be used by the students or professionals to aid them in problem solving or decision making depending on the users need. Often engineers and scientists have to make a decision based on an incomplete set of data, this book provides tools and method to aid such decision. Furthermore, the topics and methods covered in the text aid in decision making and also in determining likelihood of an event occurring. These types of information are often needed to make an educated guess, if the data is missing or hard to obtain. It also goes over the probability, that is likelihood of something occurring, an event based on the historical data.
I would have liked to see more and variety of examples after the introduction of a new topic. Furthermore the book doesn't contain answers to any of the problems that appear at the end of each chapter which is an issue. Most engineering books contain answers to at least odd number of problems but this book contains none. It is reasonably priced however I feel that color should have been used in the text to add a visual appeal to the book. Moreover, most books contain a CD to explain complex engineering problems and that component can be added for this text as well.
This book is great because it lays a foundation for engineering students and provides them with a great background in interpreting and analyzing data. Overall content wise this book is excellent which can be easily made better by adding the components that I mentioned above. I sincerely hope that this review aids in making this text better.

I found this book to be helpful in learning probability and statistics. It is generally well written with clear examples of what to do. Some of the text gets a little wordy however and is hard to follow. The examples are usually easy to follow, and I appreciate the consistency of examples from chapter to chapter, and examples that are useful for real life application. The consistency of chapter organization is also a plus. I found it easier to read through a chapter knowing the basic outline of it and what to expect from section to section. The table of contents at the beginning of each chapter is a quality that in my experience is unique to this book. It is helpful to get a feel for the chapter before you start reading, or to quickly jump to the section that you need to find. It is also useful because it is easy to get lost in the numbering of the sections each with a 3 digit identifying number. The problems are mostly well written and applicable to the chapters. They don't follow the examples as closely as I would have hoped, but that probably makes for a better teaching tool. The simulation problems look interesting for more real world application. However, the book would benefit from a section with selected answers in the back. These are useful to let the reader know if they are on the right track or not. Overall this is an excellent textbook that is very well organized, it is hard to follow at points, but its strengths ultimately outweigh its weaknesses.

The purpose of this book is to inform engineers and scientist of how to use probability, statistics, and reliability in their respective field.
This book is well organized by chapter and subsections using numerals. Its organization first introduces a new concept, then proceeds to describe it in further detail, and finally gives applicable examples of how to use these methods.

This book can provide to be a useful tool and reference to its intended audience. It is easy to find different methods and each method is well introduced with its intended purpose. I personally felt the book could be gaged for a broader audience with a small amount of added descriptive detail. For someone familiar with probability, statistics, and reliability methods and someone using this book as a reference, I feel the book is very effective. Not being an expert and not having a large amount experience in the study of probability, statistics, and reliability, I believe it would be beneficial for the book to provide a few less-technical descriptive terms. As a very basic example: The book defines the use of the cumulative mass function in this way: "The cumulative mass function is used to indicate the probability the random variable X is less than or equal to xi." This is a good definition for someone familiar with the concepts and should not be omitted. For a novice, the inclusion of an additional sentence for clarity might help. To drive the point home it might include a following sentence such as, "For example, the cumulative mass function is the chance of picking a card out of a deck that has a number on it less than or equal to 3." This describes an action the reader can relate to. As the chapters move into more and more technical detail, a plain language, nontechnical description of what the general subject is can be very helpful for a novice reader.

Overall, this book is a well written resource for scientists and engineers. With the addition of a few nontechnical details, I believe the book will be able to reach a broader audience and be more applicable to students and the less informed reader.

Probability, Statistics, and Reliability for Engineers and Scientists, written by Bilal Ayyub and Richard McCuen, is a very thorough textbook that covers all the important parts of probability and statists needed for engineers. It gives many accurate and applicable examples to its readers. All the examples are worked through very nicely, making it easy to follow for someone very new to the subject.

I would prefer if the examples are better highlighted and recognized as examples, to stand out more and draw the attention of the users that are searching for only examples. That being said, maybe adding some color, although might be more expensive, may help identify them. Also, if the spacing were a little larger in between sections it would not be as visually overwhelming.

The graphs are large and labeled really well and are often a great tool for the students to further their understanding of the material.

I like how equations are clearly written out and given a lot of room in between and after the text, making them easy to comment on with hand written notes in the margins. I also like how the equations are each numbered, making them easy to reference. I would prefer if the textbook were a little larger with respect to its surface area, thereby being overall thinner. I think this design would make the textbook more comfortable to hold and read through.

The amount of examples and review problems for each chapter make it really helpful to prepare for exams. I think it would be more beneficial if there were selected answers/solutions in the back of the book. I am often hesitant to do problems when I am not sure if they will be right, than again as it is now, it encourages students to study in groups. There are clearly arguments for both sides.

Before each new topic there is a very helpful in depth description and background of the topic to be stated that really helps the reader get the entire context of the topic. Without these sections I feel that I would be very lost.

As it says in the beginning of the text, the purpose of this book is to "1) introduce probability, statistics, reliability, and risk methods to students and practicing professionals in the engineering world and the sciences, 2) emphasize the practical use of methods, 3) establish the limitations, advantages, and disadvantages of the methods". Based on my observation, I think the goals set for this text were well achieved.

I do really like the textbook, and I think I get a very thorough understanding of the material, while seeing real life application. I would say it is a textbook worth keeping after this course as a reliable reference.

One of the greatest facets of the textbook is the clear and concise writing style. The authors present the subject manner in a way that is both easy to understand and comprehend. A strong emphasis was placed on incorporating "real world" case studies within each chapter. This allows the reader to understand the significance and relevance of the subject material in applied engineering. Examples include [but are not limited to] building/construction design, and natural hazards.

The structure and setup of each chapter aids in achieving greater reader comprehension. Each chapter begins with an introduction, providing a brief synopsis of the material to be covered. The format is deductive in nature, beginning with general topics and moving towards specific focus areas. This format is particularly organized and systematic.

An important feature of the textbook is the incorporation of the derivation of particularly useful equations. All too often, in many textbooks, the derivation of equations is left out, leaving the reader with the "final equation" only. I believe that the inclusion of derivations allows for greater comprehensiveness.

In terms of improvement of the textbook, a larger number of pictures and diagrams [when necessary] may help, although it may be difficult to add. Additionally, the availability of a soft-cover copy would reduce the cost of the textbook.

In summary, this is an excellent source of information for understanding probability, statistics, and reliability.

I recently read the first edition of this book. There are some things I understand now which I didn't understand when I read descriptions of the same material in other statistics textbooks. I didn't put forth the effort to try to understand everything the book had to say, but even my cursory reading added to my meagre but growing store of knowledge.

Ayyub provides an excellent systemic context for the exposition of reliability theory, especially as it relates to applications for decision-makers and decision-making. The mathematical basis of reliability in probability and statisitics is clearly presented and is suitable for engineering students and managers.