Rating: 
Summary: Uncovering lies in medicine, medical testing and the courts
Review: A real eye opener about how statistics can be manipulated by physicians, special interest groups and the courts
Rating:
Summary: Be an Informed Consumer in the Age of Numbers
Review: Gerd Gigerenzer has written several books dealing with "bounded rationality"--how humans use their brains to understand the world around them, make decisions, and determine the risks associated with a given course of action. This book is easily his most accessible. It is clear and easy to read, with most(but not all)the examples drawn from the field of personal health.Gigerenzer provides the simple mental tools that allow anyone to make sense of the statistics that bombard us daily in the media. It is exactly his point that one does not need to be a rocket scientist (or professional statistician) to understand the numbers used by professionals, from personal physicians to DNA experts, that affect our lives and livelihoods. If I could recommend only one book to address "numerical illiteracy," this would be it. You will learn some essential skills in a clearly informative and entertaining way.
Rating:
Summary: Be an Informed Consumer in the Age of Numbers
Review: Gerd Gigerenzer has written several books dealing with "bounded rationality"--how humans use their brains to understand the world around them, make decisions, and determine the risks associated with a given course of action. This book is easily his most accessible. It is clear and easy to read, with most(but not all)the examples drawn from the field of personal health. Gigerenzer provides the simple mental tools that allow anyone to make sense of the statistics that bombard us daily in the media. It is exactly his point that one does not need to be a rocket scientist (or professional statistician) to understand the numbers used by professionals, from personal physicians to DNA experts, that affect our lives and livelihoods. If I could recommend only one book to address "numerical illiteracy," this would be it. You will learn some essential skills in a clearly informative and entertaining way.
Rating:
Summary: EVERYone should read this!
Review: Heading for a medical exam? Wonder if those uncomfortable, expensive tests really make a difference? Skip the medical libraries and talk to the statisticians. Gigerenzer bares the truth that doctors conceal because of ignorance or greed. Every woman should read his chapter on the risks and benefits of mammograms. The rate of false positives for mammograms is a whopping ninety percent. The cost is not measured by x-ray charges alone (although a radiologist huffed out of a meeting with a gynecologist who stopped recommending mammograms -- they make big bucks from those tests!). Think of the unnecessary biopsies -- and the unnecessary surgery because biopsies have error rates too. Cancer tests do not cure or prevent cancer. They may reduce the risk of death, although a comparison between screened and unscreened populations shows that very few lives are actually saved this way. And there is no risk reduction unless early detection affords access to a cure. AIDS tests also carry risks. The rate of false positives among a healthy, "safe-sex" population is about fifty percent. The author describes horror stories of disease-free people who were mis-diagnosed. They lost jobs, homes and friends; some sued for recovery but at least one committed suicide. Our health care system spends millions on tests because both patients and doctors are ill-informed. We demand a cure and the medical system finds a way to give us the illusion of progress. It's not just the US. The author found ignorance of false positives for AIDS tests in Germany. When I lived in Canada, the provincial health system bombarded us with propaganda for mammograms. Gigerenzer has done the world a great service by writing this book and presenting data in a reader-friendly fashion. I suspect there is a human tendency to look for certainty and today's medical tests seems to be the equivalent of divining rods and astrology of three hundred years ago. Now I wish he'd take a look at academic and career tests, most of which also give a form of "false positives." We'd like a yes or no in this world, but alas, mostly we have to learn to live with the maybes.
Rating:
Summary: EVERYone should read this!
Review: Heading for a medical exam? Wonder if those uncomfortable, expensive tests really make a difference? Skip the medical libraries and talk to the statisticians. Gigerenzer bares the truth that doctors conceal because of ignorance or greed. Every woman should read his chapter on the risks and benefits of mammograms. The rate of false positives for mammograms is a whopping ninety percent. The cost is not measured by x-ray charges alone (although a radiologist huffed out of a meeting with a gynecologist who stopped recommending mammograms -- they make big bucks from those tests!). Think of the unnecessary biopsies -- and the unnecessary surgery because biopsies have error rates too. Cancer tests do not cure or prevent cancer. They may reduce the risk of death, although a comparison between screened and unscreened populations shows that very few lives are actually saved this way. And there is no risk reduction unless early detection affords access to a cure. AIDS tests also carry risks. The rate of false positives among a healthy, "safe-sex" population is about fifty percent. The author describes horror stories of disease-free people who were mis-diagnosed. They lost jobs, homes and friends; some sued for recovery but at least one committed suicide. Our health care system spends millions on tests because both patients and doctors are ill-informed. We demand a cure and the medical system finds a way to give us the illusion of progress. It's not just the US. The author found ignorance of false positives for AIDS tests in Germany. When I lived in Canada, the provincial health system bombarded us with propaganda for mammograms. Gigerenzer has done the world a great service by writing this book and presenting data in a reader-friendly fashion. I suspect there is a human tendency to look for certainty and today's medical tests seems to be the equivalent of divining rods and astrology of three hundred years ago. Now I wish he'd take a look at academic and career tests, most of which also give a form of "false positives." We'd like a yes or no in this world, but alas, mostly we have to learn to live with the maybes.
Rating:
Summary: Required reading for everyone!
Review: In a valiant effort to educate professionals and lay people alike, the author of this book clearly explains how to interpret risks and risk data (statistics) in a useful and understandable way. For example, anyone who is wondering about whether or not to undergo screening for breast cancer, prostate cancer, HIV, etc. should do themselves a great big favor and read this book. The author also discusses legal issues such as how evidence may presented in court in order to support a given side of a case just by presenting statistical data, e.g., fingerprints, DNA evidence, etc., in certain ways. In addition, the author discusses a variety of other matters from advertising gimmicks to TV game show strategies. Using the techniques given in this book, readers will be much less likely to be fooled. Clearly written in plain english and in an engaging style, this book should be required reading for everyone - from professionals who provide statistical (risk) information (they would learn how to be more clearly understood) to those receiving the information (they would learn to see through any smoke screens or awkward presentations and thus make better decisions).
Rating:
Summary: Calculated Risks by Gigerenzer
Review: The author presents some important observations about calculated
risks, probabilities and statistical test inferences. He makes
clear the necessity to understand risks clearly at the outset
of any important decision. For instance, a physician must take
into consideration "false positive " test results so that
he/she does not over-react. An over-reaction could cause the
physician to take unnecessary precautions that could do more
to endanger the patient than help. In addition, the author
cautions against fabrication of certainty or the use of
statistics to prove a predetermined result. This book is
useful in arriving at a realistic design for a statistical
test or any other test from which an important scientific
inference will be made.
Rating: 
Summary: A couple of great ideas
Review: This book illustrates two important concepts very well: Statistics confuse even intelligent people, and the meaning of "false negative" and "false positive" data, especially when reported as percentages, can be far from intuitive.
Why only three stars? Both of these ideas are thoroughly illustrated and then beaten to death by page 50 of this 300 page book. (You can get most of the information from reading one or two of the other reviews here on Amazon).
The remainder of the book uses various medical examples to make the point that a percentage of a percentage may sound more significant than it is (or less significant than it is). As Gigerenzer illustrates, doing the arithmetic to determine the actual numbers of each case represented will untangle most misunderstandings. After about a dozen of these, though, only a reader with an interest in the specific examples will remain engaged.
The writing is clear, the examples are all good, and the book does amply illustrate the quotation cited in Mark Twain's Autobiography: "There are three kinds of lies: lies, damned lies and statistics."
Rating:
Summary: Help for the Statistically Innumerate
Review: This is a serious and worthwhile explanation of how probabilities are manipulated -- in the law, in medicine, and by advertisers. It covers a lot of the same ground as "Innumeracy" and "How to Lie with Statistics" but it is less jokey and more serious in import. The author's principal argument is that probabilities are more understandable if given in terms of natural frequencies. The material is often technical, but it is written for the educated layperson and the explanations are fully understandable with some effort. Some of the author's conclusions about the benefits of certain medical tests -- mammograms and prostate tests, for example -- may be controversial. If you are ever flustered by probabilities, this is a very good place to get some grounding in the subject.
Rating:
Summary: How to interpret test results better than your Doc!
Review: This is a very clearly written book. It demonstrates many numerical errors the press, the public, and experts make in interpreting the accuracy of medical screening test (mammography, HIV test, etc...) and figuring out the probability of an accused person being guilty. At the foundation of the above confusions lies the interpretation of Baye's rule. Taking one example on page 45 regarding breast cancer. Breast cancer affects 0.8% of women over 40. Mammography correctly interprets 90% of the positive tests (when women do have breast cancer) and 93% of the negative ones (when they don't have breast cancer). If you ask a doctor how accurate this test is if you get a positive test, the majority will tell you the test is 90% accurate or more. That is wrong. The author recommends using natural frequencies (instead of conditional probabilities) to accurately interpret Baye's rule. Thus, 8 out of every 1,000 women have breast cancer. Of these 8 women, 7 will have a positive mammogram (true positives). Of, the remaining 992 women who don't have breast cancer, 70 will have a positive mammogram (false positives). So, the accuracy of the test is 7/(7+70) = 10%. Wow, that is pretty different than the 90% that most doctors believe! What to do? In the case of mammography, if you take a second test that turns positive, the accuracy would jump to 57% (not that much better than flipping a coin). It is only when taking a third test that also turns positive that you can be reasonably certain (93% accuracy) that you have breast cancer. So, what doctors should say is that a positive test really does not mean anything. And, it is only after the third consecutive positive test that you can be over 90% certain that you have breast cancer. Yet, most doctors convey this level of accuracy after the very first test! What applies to breast cancer screening also applies to prostate cancer, HIV test, and other medical tests. In each case, the medical profession acts like the first positive test provides you with certainty that you have the disease or not. As a rule of thumb, you should get at least a second test and preferably a third one to increase its accuracy. The author comes up with many other counterintuitive concepts. They are all associated with the fact that events are far more uncertain than the certainty that is conveyed to the public. For instance, DNA testing does not prove much. Ten people can share the same DNA pattern. Another counterintuitive concepts is associated with risk reduction. Let's say you have a cancer that has a prevalence of 0.5% in the population (5 in 1,000). The press will invariably make promising headline that a given treatment reduces mortality by 20%. But, what does this really mean? It means that mortality will be reduced by 1 death (from 5 down to 4). The author states that the relative risk has decreased by 20%; but, the absolute risk has decreased by only 1 in 1,000. He feels strongly that both risks should be conveyed to the public. The author shows how health agencies and researchers express benefits of treatments by mentioning reduction in relative risk. This leads the public to grossly overstate the benefits of such treatment. The author further indicates how various health authorities use either relative risk or absolute risk to either maximize or minimize the public's interpretation of a health risk. But, they rarely convey both; which is the only honest way to convey the data. If you are interested in this subject, I strongly recommend: "The Psychology of Judgment and Decision Making" by Scott Plous. This is a fascinating book analyzing how we are less Cartesian than we think. A slew of human bias flaws our own judgment. Many of these deal with other application of Baye's rule.
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