Product Description

Risk Analysis concerns itself with the quantification of risk, the modeling of identified risks and how to make decisions from those models. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability of a problem. By providing the building blocks the author guides the reader through the necessary steps to produce an accurate risk analysis model and offers general and specific techniques to cope with most modeling problems. A wide range of solved problems is used to illustrate these techniques and how they can be used together to solve otherwise complex problems.

Product Details

• Amazon Sales Rank: #197228 in Books
• Published on: 2008-05-19
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 752 pages

From the Publisher
Based entirely on proven techniques, this superb guide is designed for those who do computer modelling. Stressing the accuracy of risk modelling rather than the management of risk analysis, it provides excellent guidelines for modelling uncertainty using spreadsheets and Monte Carlo software. Features sufficient probability and statistics theory for readers to be confident of the correctness of the methods and understand when and how the theories can be used. Includes scores of graphs, charts, practical exercises and model solutions.

From the Inside Flap
The Ten Commandments to quantitative risk analysis Morgan and Henrion, 1990

• Do your homework with literature, experts and users
• Let the problem drive the analysis
• Make the analysis as simple as possible, but no simpler
• Identify all significant assumptions
• Be explicit about decision criteria and policy strategy
• Be explicit about uncertainties
• Perform systematic sensitivity and uncertainty analysis
• Iteratively refine the problem statement and analysis
• Document clearly and completely
• Expose to peer review

From the Back Cover
Risk Analysis: A Quantitative Guide is a comprehensive guide for eh risk analyst and decision maker. based on the author's extensive experience in solving real-world risk problems, this book is an invaluable aid to the risk analysis practitioner. by providing the building blocks of risk-based thinking the author guides the reader through the steps necessary to produce a realistic risk-based thinking the author guides the reader through the steps necessary to produce a realistic risk analysis and offers general and specific techniques to cope with most common and challenging risk modelling problems. A wide range of solved examples is used to illustrate these technique and how they can be put together to make the best possible risk-based decisions.

The third edition of this highly regarded text has been thoroughly updated and expanded considerably with five new chapters for the risk manager, including how to plan and assess the quality of risk analysis, as well as new chapters for this risk analysis, as well as new chapters for the risk analysis modeller on summation of random variables, causality, optimization, insurance and finance modelling, forecasting, model validation and common errors, capital investment and microbial risk assessment. This new edition provides a greater focus on business and includes applications in a wide range of different settings.

Key Features:

• Breaks down techniques into types of modelling issues (like distribution fitting, correlation and time series forecasting) and then applies them with easy-to-follow examples.
• Explains powerful and proven Monte Carlo simulation and numerical techniques for dealing with uncertainty.
• Includes recent innovations in modelling like fast Fourier transforms and copulas.
• Over 150 examples models and over 400 illustrations.
• Written in an informal manner with a practical rather than academic focus.
• Discusses the planning, uses and abuses of risk analysis.
• Includes a compendium of almost eighty distribution types and their uses.

Customer Reviews

A great primer and reference text for simulation modelling
Whether you are attempting Monte Carlo simulation for the first time or have plenty of practical experience, Vose's book is the best text available.

Vose has done a great job providing a brief but solid introduction to probability and statistics. It also serves as a great practical reference for the details and applications of all of the commonly used probability distribution functions.

He expertly summarizes each of the main steps a modeller will face in developing a model, providing very practical examples with helpful figures illustrating exactly how to implement the example in a spreadsheet.

The introduction could be improved by describing the context of his book, largerly directed towards cost analysis of projects, in the very broad field of Quantiative Risk Analysis. If I could add a section to the book, I would devote a chapter to common errors committed by the novice modeller. Minor criticisms aside, I do not hesitate in recommending this book as a reference for experts. I think it provides the fastest route up the learning curve for the novice modeller.

Excellent Text for Applied Risk Engineers
I work in the field of risk and reliability engineering and I am thoroughly impressed by this book. This is especially useful for engineers who are not used to working with probability theory. Although many of the examples are from the health sciences, the methodology can be applied to engineering problems as well. It's worth the price, though I would like to see more examples using Crystal Ball software. I would also like to see more information on probabilistic risk assessment methods like event trees and it's implementation in Excel / Crystal Ball.

Risk Analysis: A Quantitative Guide
I purchased this book to learn to write simulation equations in excel but only found it was a manual ( type book ) with good information for a very expensive software I did not have....If you have RISK software, it is a great book to have... I returned my copy w/o scanning the entire book.