Understanding risk -- Putting risk in perspective -- Risk charts : a way to get perspective -- Judging the benefit of a health intervention -- Not all benefits are equal : understand the outcome -- Consider the downsides -- Do the benefits outweight the downsides? -- Beware of exaggerated importance -- Beware of exaggerated certainty -- Who's behind the numbers?

At the beginning of the twentieth century, H. G. Wells predicted that statistical thinking would be as necessary for citizenship in a technological world as the ability to read and write. But in the twenty-first century, we are often overwhelmed by a baffling array of percentages and probabilities as we try to navigate in a world dominated by statistics. Cognitive scientist Gerd Gigerenzer says that because we haven't learned statistical thinking, we don't understand risk and uncertainty. In order to assess risk -- everything from the risk of an automobile accident to the certainty or uncertainty of some common medical screening tests -- we need a basic understanding of statistics. Astonishingly, doctors and lawyers don't understand risk any better than anyone else. Gigerenzer reports a study in which doctors were told the results of breast cancer screenings and then were asked to explain the risks of contracting breast cancer to a woman who received a positive result from a screening. The actual risk was small because the test gives many false positives. But nearly every physician in the study overstated the risk. Yet many people will have to make important health decisions based on such information and the interpretation of that information by their doctors. Gigerenzer explains that a major obstacle to our understanding of numbers is that we live with an illusion of certainty. Many of us believe that HIV tests, DNA fingerprinting, and the growing number of genetic tests are absolutely certain. But even DNA evidence can produce spurious matches. We cling to our illusion of certainty because the medical industry, insurance companies, investment advisers, and election campaigns have become purveyors of certainty, marketing it like a commodity. To avoid confusion, says Gigerenzer, we should rely on more understandable representations of risk, such as absolute risks. For example, it is said that a mammography screening reduces the risk of breast cancer by 25 percent. But in absolute risks, that means that out of every 1,000 women who do not participate in screening, 4 will die; while out of 1,000 women who do, 3 will die. A 25 percent risk reduction sounds much more significant than a benefit that 1 out of 1,000 women will reap. This eye-opening book explains how we can overcome our ignorance of numbers and better understand the risks we may be taking with our money, our health, and our lives.

"Explains how to assess and handle technical risk, schedule risk, and cost risk efficiently and effectively--enabling engineering professionals to anticipate failures regardless of system complexity--highlighting opportunities to turn failure into success."

We live in a technological world, exposed to many risks and errors and the fear of death. Know the Risk shows us how we can learn from the many errors and tragic accidents which have plagued our developing technological world.This breakthrough volume presents a new concept and theory that shows how errors can and should be analyzed so that learning and experience are accounted for. The authors show that, by using a universal learning curve, errors can be tracked and managed so that they are reduced to the smallest number possible.The authors have devoted a number of years to gathering data, analyzing theories relating to error reduction, design improvement, management of errors and assignment of cause. The analyzed data relates to millions of errors. They find a common thread between all technology-related accidents and link all of these errors (from the headline stories to the everyday accidents). They challenge the reader to take a different look at the stream of threats, risks, dangers, statistics and errors by presenting a new perspective. The book makes use of detailed illustrations and explores many headline accidents which highlight human weaknesses in harnessing and exploiting the technology we have developed; from the Titanic to Chernobyl, Bhopal to Concorde, the Mary Rose to the Paddington rail crash and examine errors over which we have little or no control. By analyzing the vast data society has collected, the authors show how the famous accidents and our everyday risks are related.The authors prove the strength of their observations by comparing their findings to the recorded history of tragedies, disasters, accidents and incidents in chemical, airline, shipping, rail, automobile, nuclear, medical, industrial and manufacturing technologies. They also address the management of Quality and losses in production, the search for zero defects and the avoidance of personal risk and danger.Stresses the importance of a learning environment for safety improvementPlaces both quality and safety management in the same learning contextLearn how to track and manage errors to reduce as quickly as possible

Too many executives think risk management is strictly for technical specialists. In Risk Intelligence: Learning to Manage What We Don’t Know, David Apgar challenges this misconception. The author explains how to raise the quality of your risk analysis—-thus enhancing your “risk IQ”—-by applying four simple rules: 1) Recognize which risks are learnable—and reduce their uncertainty by discovering more about them. 2) Identify risks you can learn about the fastest. The higher your learning speed, the more a project is worth pursuing. 3) Take on risky projects one at a time—learning about the risks underlying each before moving to the next. 4) Build networks of business partners, suppliers, and customers who can collectively manage new ventures’ risks by playing distinct roles. The book provides two tools for improving your risk IQ—the Risk Intelligence Audit and the Risk Scorecard—and concludes with a 10-step action plan for systematically raising your managerial and organizational risk IQ. Your reward? Smarter business decisions over time.

This report considers the biological and behavioral mechanisms that may underlie the pathogenicity of tobacco smoke. Many Surgeon General's reports have considered research findings on mechanisms in assessing the biological plausibility of associations observed in epidemiologic studies. Mechanisms of disease are important because they may provide plausibility, which is one of the guideline criteria for assessing evidence on causation. This report specifically reviews the evidence on the potential mechanisms by which smoking causes diseases and considers whether a mechanism is likely to be operative in the production of human disease by tobacco smoke. This evidence is relevant to understanding how smoking causes disease, to identifying those who may be particularly susceptible, and to assessing the potential risks of tobacco products.