probability model - определение. Что такое probability model
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Что (кто) такое probability model - определение

TYPE OF MATHEMATICAL MODEL
StatisticalModel; Statistical modeling; Statistical modelling; Probabilistic model; Statistical Model; Statistical models; Models, statistical; Probability models; Probability model; Model (statistics); True probability distribution
Найдено результатов: 3544
Statistical model         
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process.
Statistical Modelling         
Statistical Modelling is a bimonthly peer-reviewed scientific journal covering statistical modelling. It is published by SAGE Publications on behalf of the Statistical Modelling Society.
Linear probability model         
Linear probability models
In statistics, a linear probability model is a special case of a binary regression model. Here the dependent variable for each observation takes values which are either 0 or 1.
improbability         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
probabilistic         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
Probabilistic actions, methods, or arguments are based on the idea that you cannot be certain about results or future events but you can judge whether or not they are likely, and act on the basis of this judgment. (FORMAL)
...probabilistic exposure to risk.
ADJ: usu ADJ n
probable         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
a.
Likely, presumable, credible, reasonable, to be expected, that stands to reason.
probability         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
n. in all probability
Improbability         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
·noun The quality or state of being improbable; unlikelihood; also, that which is improbable; an improbable event or result.
Probability         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
·noun That which is or appears probable; anything that has the appearance of reality or truth.
II. Probability ·noun The quality or state of being probable; appearance of reality or truth; reasonable ground of presumption; likelihood.
III. Probability ·noun Likelihood of the occurrence of any event in the doctrine of chances, or the ratio of the number of favorable chances to the whole number of chances, favorable and unfavorable. ·see 1st Chance, ·noun, 5.
Probality         
  • Carl Friedrich Gauss
  • [[Gerolamo Cardano]] (16th century)
  • [[Christiaan Huygens]] published one of the first books on probability (17th century)
  • The probabilities of rolling several numbers using two dice.
MEASURE OF THE EXPECTATION THAT AN EVENT WILL OCCUR OR A STATEMENT IS TRUE
Probality; Probabilistic; Probabilities; Probability calculus; Improbability; Probability.; Probable; Propability; Forward probability; Applications of probability theory
·noun Probability.

Википедия

Statistical model

A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population). A statistical model represents, often in considerably idealized form, the data-generating process.

A statistical model is usually specified as a mathematical relationship between one or more random variables and other non-random variables. As such, a statistical model is "a formal representation of a theory" (Herman Adèr quoting Kenneth Bollen).

All statistical hypothesis tests and all statistical estimators are derived via statistical models. More generally, statistical models are part of the foundation of statistical inference.