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\(\qed\) Theorem (Conditional Certainty for Logical Consequences).
Theorem (Conditional Certainty for Logical Consequences) When \(A\) logically entails \(B\), \(p(B\mid A =1\).
When \(H\) entails \(E\), Conditional Certainty for Logical Consequences tells us that \(p(E\mid H =1\), so Bayes' theorem becomes: \[p(H\mid E) = p(H \frac{1}{p(E)}\] Provided \(p(E \) is less than 1, this amounts to multiplying \(p(H \) by a ratio greater than 1, which means \(p(H\mid E \) comes out larger than \(p(H \).
Similar(57)
The regularities that obtain in one's own case render the existence of such conscious states in others conditional certainties.
Mill refers to these possibilities which are conditional certainties as "permanent possibilities", thus distinguishing them from mere vague possibilities which experience gives us no warrant for reckoning upon.
These clusters are lawfully ordered; it is our knowledge of these laws or regularities that make the permanent sensations conditional certainties.
These are things, parts of the orange, existing unperceived; they are possible sensations, which, through our expectations, have become conditional certainties.
(The conditional is a condition.
VaR and CVaR are displayed as absolute values AR annualized return, SR Sharpe ratio, DD downside deviation, OR Omega ratio, VaR value at risk, CVaR conditional value at risk, TO turnover, CER certainty equivalent return.
A conditional recommendation was made where there was less certainty about the balance between desirable and undesirable effects.
Further, when our arguments do not contain conditionals, if we have certainty-preservation, probability-preservation comes free.
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