C -probability - ορισμός. Τι είναι το C -probability
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Τι (ποιος) είναι C -probability - ορισμός

MEASURE OF TOTAL VALUE ONE, GENERALIZING PROBABILITY DISTRIBUTIONS
Measure (probability); Probability Measure
  • 0-521-62128-3}} [https://books.google.com/books?id=Q1AUhivGmyUC&pg=PA149 page 149]</ref>
  • A ''probability measure'' mapping the probability space for  <math>2^3</math> events to the [[unit interval]].

improbability         
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
probabilistic         
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
Probabilistic actions, methods, or arguments are based on the idea that you cannot be certain about results or future events but you can judge whether or not they are likely, and act on the basis of this judgment. (FORMAL)
...probabilistic exposure to risk.
ADJ: usu ADJ n
probable         
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
a.
Likely, presumable, credible, reasonable, to be expected, that stands to reason.

Βικιπαίδεια

Probability measure

In mathematics, a probability measure is a real-valued function defined on a set of events in a probability space that satisfies measure properties such as countable additivity. The difference between a probability measure and the more general notion of measure (which includes concepts like area or volume) is that a probability measure must assign value 1 to the entire probability space.

Intuitively, the additivity property says that the probability assigned to the union of two disjoint events by the measure should be the sum of the probabilities of the events; for example, the value assigned to "1 or 2" in a throw of a dice should be the sum of the values assigned to "1" and "2".

Probability measures have applications in diverse fields, from physics to finance and biology.