As the author writes, this is not about literal bets, but about thinking of outcomes in terms of probabilities of what might happen, rather than an "all or nothing" Yes/No expectation. The book is easy to read, combining accounts of academic research with stories from the author's own experience and the wider world. Typical topics: (1) In thinking about our past decisions, we tend to focus on the outcomes (good or bad) rather than on our decision process --- was our decision the "percentage play" choice? And we claim credit for success but blame failure on bad luck. (2) What psychology research tells us about various aspects of predictable irrationality, such as "the stubbornness of belief" even in the face of contrary evidence. (3) Scenario planning; thinking more about long-term effects than short-term ones. (4) Most interesting (to me) were chapters on the benefits of group interaction and the CUDOS structure for group discussions -- disinterestedness and organized skepticism etc. The book provides an amiable overview of this subject with useful references to academic literature. The announced 288 pages is in fact 231 pages of main content, with comparatively few words per page, so it's actually quite a short book. And the style -- general ideas and specific memorable stories -- somehow lacks the sharp relevance to everyday life that one might hope for, which is why I gave 4 stars instead of 5. Each of the topics is covered in more depth in other non-technical books, for instance

This book is about how to make better decisions, from the trivial to the most consequential, in all endeavors of life: personal, business, political/economic forecasting, gambling, etc. It explains how to think about potential decision options, given that most entail varying degrees of risky or uncertain outcomes. Without attempting to bog the reader down in the mathematics of probability theory, the core of most textbook approaches to decision making, it clearly demonstrates how to incorporate probabilistic uncertainty into our decision-making thought processes. Since most decisions we make lead to outcomes which have an element of probabilistic uncertainty, the book's approach is relevant to all walks of life. Although Duke does not frame it this way, I think a brief explanation of two fundamentally different types of situations captured by the tool of probabilistic reasoning may be helpful. This dichotomy leads to what have been termed Objective and Subjective probabilities. Objective probabilities are those associated with outcomes that are truly random with specific known numerical probabilities governing various occurrences. For these, no amount of thinking or information on the part of those of us observing the situation can improve on understanding inherent randomness of the underlying activity leading to some outcome, i.e., the known probabilities are the best we can do in anticipating the ultimate outcome of the event. In other words, we can't improve on the odds of various outcomes however smart we may be. The best examples for this type of probability are things happening in the world of quantum mechanics, e.g., predicting the time at which a radioactive element or a neutron will decay. A close second for most practical purposes would be the outcome of the spin of a roulette wheel or the outcome of a fair roll of a pair of dice. Objective probabilities are set by the laws of nature, and, once known, the actual outcomes of a large number of repetitive observations of the same situation will lead to a predictable distribution of outcomes. Subjective probabilities, on the other hand, are probabilities we assign to various outcomes when faced with decisions leading to uncertain outcomes. They are not fixed or absolute numbers driven by the laws of nature. We may assign a numerical value to a particular outcome, e.g., a 70% chance the Patriots will win the Super Bowl against the Eagles, or, they may be qualitative rankings of possible outcomes, e.g., highly likely, pretty likely, not sure, very unlikely, etc. Three key things about Subjective probabilities are: 1. Different people thinking about the same event will usually have different estimates of the probabilistic outcomes. Subjective probabilities are not facts. They are opinions. 2. The information/knowledge the decision maker has about the situation will affect their probability estimates of different outcomes. 3. Good decision makers in many particular endeavors like poker or investing will usually, i.e., more frequently but not always, have better success in predicting uncertain outcomes than will poor decision makers. During the first couple of hundred years that mathematicians tried to develop the field of probability, they were generally focused on thinking about things they believed were governed by Objective probabilities. Even the game of poker was thought of in this way for years. Early in the 20th century, thinkers began to crystallize the idea of Subjective probabilities as distinctly different from Objective probabilities. John Maynard Keynes attempted to develop a full blown theory with his 1921 book "A Treatise On Probability". Although it had some excellent ideas, it did not succeed in laying out a firm mathematical basis for Subjective probability. This took the Italian mathematician, Bruno de Finetti, to define a mathematically rigorous treatment of Subjective probability in his 1937 book. And, thinking in bets was core to his approach. By the 1950's, de Finetti's approach became the basis for aspects of economics , game theory, and decision making under uncertainty. The latter pertains to virtually all decision making we encounter in daily life. So, what does Subjective probability have to do with bets. In short, everything. When we make a bet, we do so with a view of the chances of winning, either a qualitative view, or a quantitative view, i.e., a probability. A bet is the manifestation of one's personal estimate of the Subjective probability of the outcome you are favoring. The beauty of Duke's book is that it explains with lots of examples of how to apply Subjective probabilistic thinking in all sorts of situations without having to worry about the sound basis of the underlying mathematics. Poker is a great example of a situation in which a Subjective probabilistic assessment is critical, since trying to gauge how others will behave in playing a hand is truly a subjective, rather than objective, assessment. Thus her poker and human psychology background really do mark her as expert in teaching smart decision making for a broad audience. Since information and knowledge are key to making sound estimates of Subjective probabilities, Duke spends a lot of time on how to build a broad information base pertaining to prospective decisions, and how to guard against biases we naturally have that can cause us to resist relevant information that may rub us wrong. She implies that for lots of decisions, one can do better simply by stepping back and thinking about the pro's and con's, rather than just going on an impulse. Oftentimes we have relevant information in our head, if only we would think about it. Get external inputs as well, e.g., friends or Google. Information is key and being open to inputs that may conflict with your beliefs will improve your decision quality in the long run. Thus,the book is suitable for both the mathematically inclined and the mathematically averse. Although the math is absent, some may find some of the concepts a bit difficult or, on the surface, repetitive, as evidenced by some of the reviews posted here on Amazon. Stated differently, it may be difficult sometimes to appreciate the applicability of the advice to settings that go beyond the specific example used preceding her current point, but a little thought brings it home. No doubt, a few readers of the book will 'get it' and some won't, though they may still find some of the stories entertaining. None-the-less, I highly recommend it as worthwhile for both personal improvement, as well as supplemental reading in almost any graduate school curriculum.