Sentence examples for principles of probability from inspiring English sources

"It's beyond the normal principles of probability," he said, adding: "It nonetheless remains a hypothesis that is well founded".

The account relies on arguments that degrees of belief and degrees of desire, if rational, conform to standard principles of probability and utility.

Engineering reliability is based on the principles of probability and mathematics which is now a useful tool for estimating the proper function of systems.

Keller and her colleagues went through all the available information and assessed the uncertainties of each piece of data - applying Bayesian principles of probability to work out the most likely location of the plane.

However in order to arrive at justified inductive conclusions we cannot simply place our confidence in any of the known principles of probability theory (such as those we employ in reasoning with regard to artificial situations with bags containing red and white balls, and the like): we need some further premise.

The probabilistic or classical reliability theory is built on the principles of probability theory which introduces the probabilistic measure for evaluating confidence levels; the theory introduced in this paper is based on the possibility theory which uses a new confidence measure: the measure of possibility.

It presents an argument to supplement what Reichenbach understands to be Kant's transcendental principle of causality with a transcendental principle of probability.

Empirical knowledge thus requires both an a priori principle of causality for individual events and an a priori principle of probability to ensure that individual events can be aggregated into general laws.

Reichenbach's claim is that there is a principle of probability that has an equal status: it cannot be empirically established, but it is a precondition of empirical knowledge.

Following this path, the probability density evolution method (PDEM) has been developed by Li and Chen at the beginning of this century on the basis of the principle of probability preservation and its random event description.

The results of calibration, verification, and validation with respect to each individual model are integrated using the principles of conditional probability and total probability, and propagated through the Bayesian network in order to quantify the overall system-level prediction uncertainty.