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.

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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.

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Risk Analysis: A Quantitative Guide

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