objective probabilities


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objective probabilities

[əb′jek·tiv ‚präb·ə′bil·əd·ēz]
(statistics)
Probabilities determined by the long-run relative frequency of an event. Also known as frequency probabilities.
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Let there be J possible outcomes in a lottery defined over objective probabilities.
As Wilkinson 1 points out, the objective probabilities do not apply to the research hypotheses because these have no associated population to which an objective probability can be applied.
The second is whether prior beliefs regarding policy success influence a person's support for mitigation policy when objective probabilities of policy success are presented.
Kerr's most egregious error, however, is a different one: his assumption that the probable cause inquiry inherently involves an assessment of objective probabilities.
In addition, it is mentioned that some authors, basing their ideas on the exchangeability property, on the principles of the representation theorem and on its interpretation in the ambit of ergodic theory, which allows to show that the probability distribution of a stochastic process in certain conditions, can be defined in terms of averages in the time domain, raised the possibility of the existence of objective probabilities that have a physical meaning and therefore are not liable to subjective interpretation.
Savage (1954)--building on that of von Neumann and Morgenstern (1944)--presented, to me among many others, a convincing axiomatic argument that, in acting under uncertainty, one should maximize expected utility using probability beliefs where objective probabilities are not know.
It is a piece of well-received philosophical common sense that there is no room in a deterministic theory for objective probabilities.
To the extent that the betting public acquire race-specific information to inform their assessment of the true chances of individual runners, the actual degree of bias will depart from this limiting case, and the proportions bet will approach more closely the distribution of objective probabilities.
Most of the "critics" classical approach to probability of generating risk-generating events have turned against "objectivity": In tests conducted studies and also appeared many argue that is not a random phenomenon a phenomenon that can be measured using objective probabilities.
Aversion to loss Behavioral finance Complacency Decision Decision making Defensive avoidance Deterministic model Framing Gambler's fallacy Habit Herding Heuristic Hot hand fallacy House money Ignoring the base rate Maximization Mental accounting Mental accounts Objective probabilities Optimization Overconfidence bias Panic reactions Prospect Theory Regression to the mean Regret avoidance Representativeness Satisficing Stochastic modeling Subjective probabilities Traditional decision making
That is: (1) each choice, Ai, by the actor can be represented as a lottery over possible worlds (where the probabilities in the lottery are construed as representing either the actor's beliefs or the objective probabilities, depending on whether the expected moral goodness account is subjective or objective); (2) the comparative moral goodness of possible worlds can be represented by a numerical "goodness" function; (3) for each choice, an expected moral goodness number can be calculated by using the probabilities in the matching lottery to discount the goodness of the various possible outcomes and then aggregating; and (4) the morally appropriate choice is the choice with the largest expected goodness.
The divergence between subjective and objective probabilities can cause trouble.