If so, why? the proportion of those who have a given condition, is lower than the test’s false positive rate, even tests that have a very low chance of giving a false positive in an individual case will give more false than true positives overall. Be able to organize the computation of conditional probabilities using trees and tables. Base rate fallacy, also called base rate neglect or base rate bias, is a formal fallacy.If presented with related base rate information (i.e. When the incidence of a disease in a population is low, unless the test … According to Wikipedia (again) 65 % of people experience some form of lactose intolerance (P (Li) ) . medical tests, drug tests, etc. I do not claim any generalised success in other sectors but I'm working on it. 2. Bayes (in green) was sitting was sitting with his back to plain table, with a book and pen. By the way, I thought that what you said here: Seems to me that your thought process leads to the idea of emulating investment heroes - "What would Warren Buffett do?" I think that is the rational response to the Bayesian insights. The rate at which something happens in general is called the base rate. Better still when my logic and  high Stockrank numbers happen to coincide, or is this just another random event? The base rate fallacy, also called base rate neglect or base rate bias, is a formal fallacy.If presented with related base rate information (i.e. Tom, Thanks for the feedback - I quite enjoyed writing this one. "So in the example given we were directed to consider that although satanists often have certain characteristics their numbers are small. Be able to use Bayes’ formula to ‘invert’ conditional probabilities. Understand the base rate fallacy thoroughly. Base-Rate Fallacy in Intrusion Detection 4. Easy Definition of Base Rate Fallacy: Don't think "99% accurate" means a 1% failure rate.There's far more to think about before you can work out the failure rate. By looking in the table we can simply extract the data: posterior = (prior * probability of prior given new evidence) / all evidence. But if the Base Rate is higher, it is well above zero. I have already explained why NSA-style wholesale surveillance data-mining systems are useless for finding terrorists. If I was to employ such a strategy, my worry would be that I've essentially replaced one forecasting problem (the stock picking problem) with another almost identical forecasting problem (the sector picking problem). A witness claims the cab was green, however later tests show that they only correctly … Why are doctors reluctant to randomly test or screen patients for rare conditions? Intuitively, one might think that it is not much different from the example above. Consumption was growing strongly. But, the big but in general, hospitals double check some positive results and you therefore could trust your hospitals. Using Baye's theorem, we get actual probabilities of competing hypotheses. Bayesian models are more intuitive to correctly specify than frequentist tests. It is turning out to be the same market beating success story in the UK with many of the Stocko Guru and Stockrank screen selections to date. Good luck with your investing, We can avoid this fallacy using a fundamental law of probability, Bayes’ theorem. Thanks, Let’s suppose that there is a test for telling you if you will develop lactose intolerance in your life. Base rate fallacy, or base rate neglect, is a cognitive error whereby too little weight is placed on the base, or original rate, of possibility (e.g., the probability of A given B). If Hand Dare events, then: P(P(HjD) = DjH)P(H) P(D) Our view is that Bayes’ theorem forms the foundation for inferential statistics. Value stocks, for example - it seems self evident that buying dollars for 50 cents will always prove to be profitable. Not a single scientifically hold belief for something, let’s say that mitochondria are the “powerhouses” of the cell, is based on only one assumption or observation. In fact, each new experiment and new observation (given that the experimental parameters allow a deduction of a new direction) updates our beliefs, i.e. Footnotes. Base-Rate Fallacy in Intrusion Detection3. Base rate fallacy. Have a good evening, 8.5 The Base Rate Fallacy. [This must greatly reduce the probability of any companies in his portfolio going bankrupt. ( Log Out /  I'm not saying I disagree, I'm just curious as to how you (or anyone else?) The evidence would suggest that experts and amateurs alike are poor forecasters whether it comes to company earnings or macro events - it seems the future just isn't all that clear, whatever the scale! Population growth was strong. This and other experiments led eventually to a mathematical formulation of Bayes theorem. I came across the US Guru screens on AAII whose performance data goes back 10 years or more: http://www.aaii.com/stock-screens?a=menubarHome - Click on the different year tags for % gain rankings. In this case, throwing a coin will more accurately tell, if you have the disease. Thus, it is not at all clear that Bayes' theorem deserves the … 1 For a more extensive treatment see one of John Kruschke’s blog posts. Answer to the Thought Experiment: The exact answer to this problem depends upon what percentage of the population is homosexual. Again I think this must improve the probability of long-term success of the stocks in his portfolio.] If so, why? P( H | E ) = probability of H(ypothesis) given that E(vidence) [so “|” means “given that”] or in other words, the probability that the hypothesis holds, given that the evidence is true. In relation to stockpicking I am reminded of the book, "Simple, But Not Easy" - Stockpicking is simple but its not easy to be successful. The base rate fallacy and its impact on decision making was first popularised by Amos Tversky and Daniel Kahneman in the early 1970’s. He avoids start-ups and biotech or exploration stocks. - He tends to buy stocks of small, rather than big, companies. What I'm trying to say is that if builders or banks are in a period of decline then the answer is to avoid those sectors not to invest time and energy trying to pick the best stocks therein. Koehler: Base rate fallacy superiority of the nonnative rule reduces to an untested empirical claim. generic, general information) and specific information (information pertaining only to a certain case), the mind tends to ignore the former and focus on the latter.. Base rate neglect is a specific form of the more general extension neglect. General explanation from Wikipedia: When the incidence, i.e. The axioms of probability are these three conditions on the function P: 1. The chance that somethingin the outcome space occurs is 100%, because the outcome space contains ever… Although John Lee obviously has great skill as a stock-picker, I think it is very interesting [in the light of this excellent article by Tom Firth on Bayes Theorem and conditional probability] how John Lee has increased the odds of long-term success by the rules he uses to reduce the size of the pool of stocks that he picks from. Why do knowers of Bayes's Theorem still commit the Base Rate Fallacy? A classic explanation for the base rate fallacy involves a scenario in which 85% of cabs in a city are blue and the rest are green. might address those concerns. As with the base rate fallacy, this process is best outlined with an example, for which I will use example 2 on the same Wikipedia page linked above. Let A and B be events. I cannot find any of that reflected in your discussion of John Lee's approach that will help others to emulate it. 1. It is remarkable just how many of these US "Guru" screen selections have beaten the US market, without direct human intervention. Bayes’ theorem: what it is, a simple example, and a counter-intuitive example that demonstrates the base rate fallacy. 7. In my opinion just a few successful calls which are used as the basis for significant investments and which are held for significant periods can deliver life changing returns. A person receiving a positive test could be around 97.7% confident that it correctly indicates the development of the lactose intolerance. The base rate fallacy is a specific mistake of this type, that is, a failure to use all relevant information in an inductive inference. Quite a few of his examples relate to gambling, but they could equally as well be attributed to our "investment" decisions. The probability of every event is at least zero. really summarised the idea concisely and in very simple language - I may have to borrow your phrasing in the future! In fact at the moment I have a stockpicked quality/momentum type portfolio and a more recently a rules based high Stockrank portfolio to see what happens. When the incidence, i.e. Example 1 given on the Wikipedia page is clear and easy to picture. [Again I think this must improve the probability of out-performance by those stocks of the market as a whole.] If a woman has breast cancer, the probability that she tests positive is 90% ("sensitivity" or reliability rating). It shows how a prior assumption (called prior probability) is updated in a light of new evidence. Our prior belief of having the disease is just the distribution of the disease in the population, so 65% or 0.65 (P (Li)). Conclusion5. (The right sector is the one with the most favourable base rate. ) Therefore I think it makes sense for me to apply Bayesian thinking to an area that I might consider to be a little more timeless. So stockpicking for me its understanding that I have all the human bias's and need all the help I can get! 5. Change ), How to do Science: Bayes Theorem and the base rate fallacy, Distinction between Frequentist and Bayesian Approaches, being identified positive, given that you’re sick, being identified positive, given that you not carry the disease, being identified negative, while not carrying the disease, being identified negative, but actually having the disease. Why do knowers of Bayes's Theorem still commit the Base Rate Fallacy? This means that the odds are still overwhelmingly in favour of John being a Christian. The English statistician Thomas Bayes has done an interesting experiment on how to visualize that. Tom. The theorem concerns the incorporation of new information into old, in order to accurately determine the revised probability of an event in light of the new information. (P(S) = 100%. Bayes' theorem for the layman. Now you have pointed it out it it seems blindingly obvious! This is illustrated by the fact that he was one of the first investors in the UK to have an ISA portfolio worth a million pounds. Let’s say we have two events and . One criticism or thing to notice, is that the whole calculation is dependent on the “prior”, the starting hypothesis, that is waiting to be updated by the new evidence. Base Rates and Bayes’ Theorem. In short, it describes the tendency of people to focus on case specific information and to ignore broader base rate information when making decisions involving probabilities. But if the individual company was in a sector that was going downwards then even a strong outperformance of its peers might still deliver a dismal performance in absolute terms. I am familiar with Bayes theorem and I am a big fan of StockRanks but I hadn't made the connection. In that case, each new ball (new information) updated his belief. Here’s a more formal explanation:. We write that the probability of the event is . I'd look at things from a different angle. Base rate fallacy example. Bayesian inference tells us what we want to know. Consequently there are more Christians who look like satanists than there are satanists who look like satanists. I was using Lord John Lee as an example of someone who been extremely successful at investing over many years, and whose success supports what Tom Firth wrote in that section. You could if you wished simply buy the sector in toto by using a collective or by buying a basket of shares. This idea is linked to the Base Rate Fallacy.