We can also translate this into the average number of notes each person has squirrelled away:. Available here. These measures are used when faced with contingency tables:. The odds of success is the ratio of the probability of success to the chance of failure :. The probability of having a disease for the group can be found by restricting attention to the row restrict attention to the people who have the trait and working out what proportion of those people have the disease:.

Hence the odds of disease for patients is:. An odds ratio greater than 1 indicates that the disease more likely to occur in the group than the group.

## "the game of our lives by peter guzlowski"

Similarly, an odds ratio less than 1 indicates that the disease is less likely to occur in the group. The relative risk is a measure of the influence of risk on disease. A relative risk of 1 means there is no difference in risk of contracting the disease between the two groups. A relative greater than 1 means the disease is more likely to occur in the group than in the group. A relative risk less than 1 means the disease is more likely to occur in the group than in the group.

For example a relative risk of 2 would mean that people would be twice as likely to contract the disease than people from the group. It is often used to compare the risk of developing a disease in people not receiving a new medical treatment or receiving a placebo versus people who are receiving an established treatment. Ah, this makes sense. I just set the hypothetical poop rate at every 12 minutes for the sake of an even number, and reports of compulsive over feeders in NYC. Very good, now we're in business. Let us assume that pigeons poop on average 5 times per hour.

In the original formula. The breaking point where it is more likely than not to get hit is a little over 12 hours trial and error with different values of N; can also be computed by using so-called "logarithms". There are essentially two different ways of computing a probability like the one you are asking for. The first is the way we have done it, using a mathematical model where one makes certain assumptions pigeons fly around randomly, are evenly distributed over an area, etc.

The model has some parameters like a, A, and N, and once these can be estimated from data, we compute our probability.

The other way is to estimate the probability directly by using data on the event we are interested in. Here, we could simply ask a number of people if they have been pooped upon akin to an opinion poll , or we could do an experiment and send out a number of people to walk around for some time and then inspect them for poop.

This could also be a way of validating our model, to make sure observed numbers are reasonably consistent with our predictions. For example, if people are out for 2 hours, our model says that we expect 20 of them to be hit by poop. If we send out people and the number of unlucky bastards deviate very much from 20, such as 0 or 50, we would suspect our model is not that great. In reality, N must be an integer. In our formula, however, it does not necessarily come out to one.

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For example, if you are out for half an hour,. This is because our N is really an average, or so-called "expected value" whereas the real N is a "random variable," meaning that its value varies. A pigeon poops on average 5 times per hour but in a given hour, the actual number of poops may be 0,1, More sophisticated modeling can be done using so-called "Poisson processes" to describe pooping events.

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Will you also provide tips on how to get rid of pigeon poop stains from your favorite linen jacket? So in that case, frequent walkers have a very good chance of encountering a pooping event about once a month? As for the stain… I made a few phone calls and am finding a curious disparity. Linen companies all advise machine washing on a cold gentle cycle and air dry.

Law of large numbers - Probability and Statistics - Khan Academy

Dry cleaners say that the only possible way is to dry clean it. The item Probabilities : the little numbers that rule our lives, Peter Olofsson represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Anaheim Public Library. Creator Olofsson, Peter, Language eng.

## Probabilities - E-bok - Olofsson Peter Olofsson () | Bokus

Publication Hoboken, N. Extent ix, pages. Isbn Label Probabilities : the little numbers that rule our lives, Peter Olofsson Instantiates Probabilities : the little numbers that rule our lives Publication Hoboken, N. Subject Probabilities -- Popular works Genre Popular works.

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