title: [Probability in medicine].
abstract: The term "probability", apparently vague, is defined as the ratio of favourable and all cases, e. g. 1/4. Sometimes is expressed as "odds", in the above example 1:3. Mathematical (a priori) probability is calculated according to the following consideration: during accidental tossing of an intact coin the probability of head is 1/2. Statistical (a posteriori) probability is assessed experimentally. If randomization is not respected, the result is doubtful. We call it bias. Probabilities are multiplied (added) if one and (or) another phenomenon should occur. Phenomena which occur or do not occur are frequently governed by binomial division. According to the law of large numbers the a posteriori probability will become the closer to the a priori probability, the larger the number of experiments. Forecasts based on probability are made possible by interferential statistics. In this respect they differ from mere statistical description. Thus optimal decision is achieved under conditions of uncertainty, typical for medicine. This applies to diagnosis as well as treatment. In this way a cut-off value can be selected for a given diagnostic test to achieve an optimal combination of the resulting sensitivity and specificity and the probability of disease (health) in case of a positive (negative) finding can be expressed. The results of statistical testing (e. g. the effectiveness of treatment) is as a rule presented by means of the probability value p, as compared with error alpha which should be assessed in advance. It is, however, necessary to respect also an alternative hypothesis. The latter is unfortunately formulated only rarely.
authors.forename: M
authors.initials: M
authors.lastname: Mikulecký
mesh_terms: D011336:Probability; D011897:Random Allocation