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The ratio of probability of occurrence to nonoccurrence of an event.
[pl. of odd, fr. M.E. odde, fr. O.Norse oddi, odd number]


In statistics, the probability that an event may appear or occur. This probability is estimated from known rates of occurrence of the event in a specific setting, e.g., from the known number of patients with a particular disease on a particular island. In practice most patients do not live on islands, and many have diseases whose presentation varies from the norm. The use of odds in health care always implies some degree of probability rather than of proof.


a method of expressing probability, e.g. at odds of 3 to 2 this can be converted to conventional terminology by using each number as the numerator and the sum of them as the denominator, i.e. 3/5, 2/5 or 60% or 40% or 0.6, 0.4. The odds are quoted as for or against. So that at odds of 3 to 2 the chances for an event happening are 3/5. The odds against it happening are 2/5.

posterior odds
probability determined after consideration of the results of a study.
odds ratio
the ratio, used particularly in case-control studies, estimates the chances of a particular event occurring in one population in relation to its rate of occurrence in another population.

Patient discussion about odds

Q. I have weak pelvic muscles.. Ive not had any children or anything like that. And im only 20. Isnt it abit odd It dont help one little bit when you have bladder problems(and struggle to control the flow)

A. Thank you for the answer Lucy, however i forgot to mention i have actually been doing P

More discussions about odds
References in periodicals archive ?
The value of posterior odds ratio also decreases for all index series.
Using this model the analysis is worked out and posterior odds ratio is evaluated.
Table 3 showed the posterior odds ratio, coefficient of determination, least square estimate of autoregressive parameter and coefficient of quadratic time trend and their standard error.
The posterior odds ratio is less than one in all cases so all the series are trend stationary.
Now remember the simple formulation of Bayes' Theorem, that the posterior odds equal the prior odds times the likelihood ratio.
Under the assumption of prior even odds, the posterior odds would also be 1000 to 1which seems to be sufficient for conviction.
To justify conviction, the juror would have to reach high posterior odds, say 99:1.

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