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Conditional probability
| Glossary of Statistical Terms |
- Suppose we are interested in the probability that some event a occurs, and we learn that the event b occurred. how should we update the probability of a to reflect this new knowledge? this is what the conditional probability does: it says how the additional knowledge that b occurred should affect the probability that a occurred quantitatively. for example, suppose that a and b are mutually exclusive. then if b occurred, a did not, so the conditional probability that a occurred given that b occurred is zero. at the other extreme, suppose that b is a subset of a, so that a must occur whenever b does. then if we learn that b occurred, a must have occurred too, so the conditional probability that a occurred given that b occurred is 100%. for in-between cases, where a and b intersect, but b is not a subset of a, the conditional probability of a given b is a number between zero and 100%. basically, one "restricts" the outcome space s to consider only the part of s that is in b, because we know that b occurred. for a to have happened given that b happened requires that ab happened, so we are interested in the event ab. to have a legitimate probability requires that p(s) = 100%, so if we are restricting the outcome space to b, we need to divide by the probability of b to make the probability of this new s be 100%. on this scale, the probability that ab happened is p(ab)/p(b). this is the definition of the conditional probability of a given b, provided p(b) is not zero (division by zero is undefined). note that the special cases ab = {} (a and b are mutually exclusive) and ab = b (b is a subset of a) agree with our intuition as described at the top of this paragraph. conditional probabilities satisfy the axioms of probability, just as ordinary probabilities do.
- Условная вероятность
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Вероятность условная, русский
Вероятность события при условии, что произошло другое событие. если d и e — два события, а р (…) — «вероятность (…)», то условная вероятность d при условии, что произошло е, обозначается как р(d|е), где вертикальный штрих означает «при условии»; она равна р(d и е) / р (е). событие е является «обусловливающим событием». ув подчиняются всем аксиомам теории вероятности. cм. также ббайеса теорема; вероятностей теория.
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Conditional, английский
- Условный
- A условный | n 1 усло- вие2; 2 грм. а) условное наклонение (син. ~ mood), б) условная связь (син. ~ conjunction); 3 лог. условное высказывание mood, sentence
- In probabilistic expert systems, a collection of conditional distributions for the same group of variables (referred to as the head) over all of the states of a conditioning set of variables (referred to as the tail). the conditional distribution of height and weight for various mutually exclusive groupings of age and sex would be a conditional, with height and weight as the head variables and age and sex the tail variables. see also: slice.
- A control structure such as an if-statement or case-statement that conditionally executes a block of code
Conditional (adj), английский
Of, pertaining to, or characteristic of an action or operation that takes place based on whether or not a certain condition is true.
Conditional (parameter), английский
Conditional addition, английский
Условное сложение
Conditional assembly, английский
Условная компоновка программы; условное ассемблирование conditional assembly expressionвыражение условного ассемблирования
Conditional assembly instruction, английский
Команда условного ассемблирования
Conditional association, английский
Условная ассоциация
Conditional behavior, английский
Обусловленное поведение
Conditional block, английский
Условный блок
Conditional branch, английский
- Условное ветвление; условный переход
- An element of workflow logic that defines an alternative condition and action or additional steps, in cases when the criteria in a condition element are not met. a logical ‘else-if-then’ statement in a workflow.
Conditional branch instruction, английский
Команда условного ветвления; команда условного перехода
Conditional branching, английский
Ветвление по условию
Conditional breakpoint, английский
Условный останов; условная точка останова; точка останова по условию; команда условного останова
Conditional breakpoint instruction, английский
Команда условного останова
Conditional c component, английский
Conditional call, английский
Applies mainly to convertible securities. circumstances under which a company can effect an earlier call, usually stated as percentage of a stock`s trading price during a particular period, such as 140% of the exercise price during a 40-day trading span.
Conditional call options, английский
A protective guarantee that, in the event a high yield bond is called, the issuing corporation will replace the bond with a noncallable bond of the same life and terms as the bond that is being called.
Conditional clause, английский
Условное предложение
Conditional color, английский
Условный цвет
Conditional comment, английский
Условный комментарий
Conditional commitment, английский
Interested, английский
Probability, английский
- Probability can be generally defined as a measure of how likely some event will occur. the event could be an explosion, a lottery win or perhaps cancer induction. mathematically speaking, the value of probability varies between 0 and 1 where 0 means an ev
- Вероятность. возможность.
- The probability of an event is a number between zero and 100%. the meaning (interpretation) of probability is the subject of theories of probability, which differ in their interpretations. however, any rule for assigning probabilities to events has to satisfy the axioms of probability.
- Вероятность
- Вероятность probability sample, syn. random sample
- Вероятность. мера случайности появления конкретного события. например, вероятность случайного выбора из популяции человека с конкретным качеством соответствует доле людей в популяции, обладающих этим качеством.
- Вероятность; возможность
- Вероятность; обеспеченность (гидрологической величины) ~ of no-failure вероятность безотказной работы
- Probability is a method for representing uncertainty about propositions or events. it represents the uncertainty about a proposition on a scale from 0 to 1, with a 0 representing complete certainty that the proposition is false or an event will not occur and a value of one will represent the opposite. formally, a probability measure is one that follows kolmogorov`s axioms. there are two main schools of thought on the meaning of probability. frequentists take a narrow interpretation of probability allowing only hypothetically repeatable events or experiments as being quantifiable by probability, while bayesians take a broader interpretation that allows reasoning about "one-shot" events and propositions based on the current knowledge about nature. the bayesian interpretation is most commonly used in artificial intelligence, while the frequentist interpretation is most commonly taught in statistics courses. the label "bayesian" arises from the central role that the bayes theorem plays in this use of probability. it allows one to reason from effects to causes and encourages the use of probability measures to describe supposedly fixed events or propositions which frequentists disallow. the probability for these events reflects one`s state of knowledge about the event, rather than being an assertion that the unknown event can vary. for example, a bayesian would have no qualms about making statements about the probability that a given die, rolled and hidden from his sight is, for example, a six. a frequentist would be unable to make such a statement, preferring to talk about his confidence in the method when applied to a hypothetically large number of repeated experiments. in the end, they would act in similar ways. when the long run data are available, bayesians and frequentists end up with the same estimates. see also: bayes theorem, kolmogorov`s axioms.
- Вероятность. математическое измерение возможности появления неко-его события, выраженное в виде дроби или процента [30]. значения статистической вероятности лежат в пределах от 1 или 100 процентов (всегда) до 0 или 0 процентов (никогда) [20]. наибольшее приближение к истинной вероятности дает относитель-ная частота события, полученная на основе большой серии измерений или результа-тов [33]. вероятность может быть также определена как выражение в некоторой неопределимой форме "степени уверенности" или как предельная частота события в бесконечной случайной последовательности [49].
- The likelihood of something happening. for example, sale being made.
- Вероятность. математическое измерение возможности появления некоего события, выраженное в виде дроби или процента [30]. значения статистической вероятности лежат в пределах от 1 или 100 процентов (всегда) до 0 или 0 процентов (никогда) [20]. наибольшее приближение к истинной вероятности дает относительная частота события, полученная на основе большой серии измерений или результатов [33]. вероятность может быть также определена как выражение в некоторой неопределимой форме "степени уверенности" или как предельная частота события в бесконечной случайной последовательности [49].
- The relative likelihood of a particular outcome among all possible outcomes.
- Likelihood that an event may occur, expressed as a number between 0 and 1.
Additional, английский
- Дополнительный 33
- Дополнительный; добавочный
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Sample mean, английский
The arithmetic mean of a random sample from a population. it is a statistic commonly used to estimate the population mean. suppose there are n data, {x1, x2, … , xn}. the sample mean is (x1 + x2 + … + xn)/n. the expected value of the sample mean is the population mean. for sampling with replacement, the se of the sample mean is the population standard deviation, divided by the square-root of the sample size. for sampling without replacement, the se of the sample mean is the finite-population correction ((n−n)/(n−1))½ times the se of the sample mean for sampling with replacement, with n the size of the population and n the size of the sample.
Regression toward the mean, regression effect, английский
Suppose one measures two variables for each member of a group of individuals, and that the correlation coefficient of the variables is positive (negative). if the value of the first variable for that individual is above average, the value of the second variable for that individual is likely to be above (below) average, but by fewer standard deviations than the first variable is. that is, the second observation is likely to be closer to the mean in standard units. for example, suppose one measures the heights of fathers and sons. each individual is a (father, son) pair; the two variables measured are the height of the father and the height of the son. these two variables will tend to have a positive correlation coefficient: fathers who are taller than average tend to have sons who are taller than average. consider a (father, son) pair chosen at random from this group. suppose the father`s height is 3sd above the average of all the fathers` heights. (the sd is the standard deviation of the fathers` heights.) then the son`s height is also likely to be above the average of the sons` heights, but by fewer than 3sd (here the sd is the standard deviation of the sons` heights).
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