Possibility theory and conditional probability offer complementary perspectives for modelling uncertainty, with each framework contributing distinct advantages. Possibility theory, rooted in fuzzy set ...

The probability that a tennis player wins the first set of a match is \(\frac{3}{5}\). If she wins the first set, the probability that she wins the second set is \(\frac{9}{10}\). If she loses the ...

90 pupils were asked whether they owned a laptop or a tablet device. 52 said they owned a laptop. 45 said they owned a tablet. 23 said they owned both. Find the probability that a pupil chosen at ...

Explain why probability is important to statistics and data science. See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. Joint probability teaches us to calculate combined outcomes.

Probability is the theory that allows us to make an inference from a sample to a population. It provides the mathematical and theoretical basis for quantifying uncertainty. Probability is also used ...

a priori Probability: the probability that we determine from knowing the process by which the uncertain event happens (by logically examining existing information). Certain Event: event that is sure ...

“One of the basic axioms of the rational theory of decision under uncertainty is Savage’s (1954) sure-thing principle (STP). It states that if prospect x is preferred to y knowing that Event A ...