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Multiplication rule

Glossary of Statistical Terms
    The chance that events a and b both occur (i.e., that event ab occurs), is the conditional probability that a occurs given that b occurs, times the unconditional probability that b occurs.




Multiplicatio, латинский

Multiplicatio [onis, f], латинский

Multiplication, английский

Multiplication - free digital filter, английский
    Цифровой фильтр, функционирующий без выполнения операций умножения 7-2 - 51


Multiplication algorithm, английский
    Алгоритм умножения


Multiplication assignment operator, английский
    Операция умножения и присваивания


Multiplication avalanche des porteurs de charge, французский

Multiplication factor, английский

Multiplication operator, английский
    Операция умножения; знак операции умножения


Multiplication rule., английский
    The chance that events a and b both occur (i.e., that event ab occurs), is the conditional probability that a occurs given that b occurs, times the unconditional probability that b occurs.


Multiplication sign, английский
    The a— character.


Multiplication table, английский
    Таблица умножения


Multiplicative inverse, английский
    Мультипликативная инверсия; инверсия относительного умножения


Multiplicative model, английский

Multiplicativus, a, um, латинский

Multiplicator, английский

Multiplicator [oris, m], латинский

Rule, английский
  1. To excel at something. example when dr. peikoff appeared on a radio talk show to discuss his views on the terrorist crisis, he was bewildered by a caller who told him, dr. peikoff, you _rule_!

  2. An established standard, guide, or regulation

  3. An alarm management subsystem that uses rules to perform specific actions when an event occurs.

  4. Правило

  5. P=l x d, in which, p = prism power; l = lens power; and d = decentration (in centimeters).

  6. An instrument having straight edges, usually marked off in inches or centimeters and fractions thereof; used for measuring distance and for drawing straight lines. run 837

  7. N правило agreement, application, ignorance, restriction, subcategorization base ~ базовое правило bayes ~ правило байеса branching ~ правило ветвления categorial ~ категориальное правило constitutive ~ тра конститутивное правило3 (ант. regulative ~; дж. сёрль ) context-free ~ контекстно-свободное правило context-sensitive ~ контекстно-связанное пра- вило lexical ~ лексическое правило morphophonemic ~ морфонемное правило orthographic ~ орфографическое правило 1 компонент слога: гласный и согласный или консонантная группа, следующие за ним. 2 артикуляция звуков, при которой губы вытягиваются вперед и прини- мают форму круглого отверстия – колечка. 3 регулирует деятельность, существовавшую до него, – деятельность, существование которой логически независимо от существования пра- вила (например, правила этикета). rule 79 segment phonetic ~ фонетическое правило projection ~ правило проекции redundancy ~ правило избыточности regulative ~ тра регулятивное правило1 (ант. constitutive ~; дж. сёрль ) rewriting ~ правило подстановки selectional ~ правило селекции semantic ~ семантическое правило spelling ~ орфографическое правило subcategorization ~ правило субкатегоризации strict subcategorization ~ правило строгой субкатегоризации transformational ~ трансформационное правилоrule rule-governed a регулируемый правилами creativity

  8. A line of varying thickness from hairline to wide


Rule, английский
    To excel at something. example when dr. peikoff appeared on a radio talk show to discuss his views on the terrorist crisis, he was bewildered by a caller who told him, dr. peikoff, you _rule_!


Rule, английский

Conditional, английский
  1. Условный

  2. A условный | n 1 усло- вие2; 2 грм. а) условное наклонение (син. ~ mood), б) условная связь (син. ~ conjunction); 3 лог. условное высказывание mood, sentence

  3. 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.

  4. A control structure such as an if-statement or case-statement that conditionally executes a block of code


Probability, английский
  1. 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

  2. Вероятность. возможность.

  3. 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.

  4. Вероятность

  5. Вероятность probability sample, syn. random sample

  6. Вероятность. мера случайности появления конкретного события. например, вероятность случайного выбора из популяции человека с конкретным качеством соответствует доле людей в популяции, обладающих этим качеством.

  7. Вероятность; возможность

  8. Вероятность; обеспеченность (гидрологической величины) ~ of no-failure вероятность безотказной работы

  9. 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.

  10. 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].

  11. The likelihood of something happening. for example, sale being made.

  12. 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].

  13. The relative likelihood of a particular outcome among all possible outcomes.

  14. Likelihood that an event may occur, expressed as a number between 0 and 1.


Unconditional, английский
    Безусловный


Chi-square curve, английский
    The chi-square curve is a family of curves that depend on a parameter called degrees of freedom (d.f.). the chi-square curve is an approximation to the probability histogram of the chi-square statistic for multinomial model if the expected number of outcomes in each category is large. the chi-square curve is positive, and its total area is 100%, so we can think of it as the probability histogram of a random variable. the balance point of the curve is d.f., so the expected value of the corresponding random variable would equal d.f.. the standard error of the corresponding random variable would be (2×d.f.)½. as d.f. grows, the shape of the chi-square curve approaches the shape of the normal curve. this page shows the chi-square curve.


Central limit theorem, английский
  1. The central limit theorem states that the probability histograms of the sample mean and sample sum of n draws with replacement from a box of labeled tickets converge to a normal curve as the sample size n grows, in the following sense: as n grows, the area of the probability histogram for any range of values approaches the area under the normal curve for the same range of values, converted to standard units. see also the normal approximation.

  2. Центральная предельная теорема

  3. The law of large numbers states that as a sample of independent, identically distributed random numbers approaches infinity, its probability density function approaches the normal distribution. see: normal distribution.

  4. The mean of a sample of data having any distribution converges upon a normal distribution as the sample size tends to infinity.