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Probability theory term
levels: discrete probabilities, probability density functions, and measure theory. Conditioning leads to a non-random result if the condition is completely
Conditioning_(probability)
Topics referred to by the same term
conditioning, air conditioning in a vehicle Ice storage air conditioning, air conditioning using ice storage Solar air conditioning, air conditioning
Conditioning
Probability of an event occurring, given that another event has already occurred
interpretation of probability. The conditioning event is interpreted as evidence for the conditioned event. That is, P(A) is the probability of A before accounting
Conditional_probability
Concept in probability theory
In probability theory, regular conditional probability is a concept that formalizes the notion of conditioning on the outcome of a random variable. The
Regular conditional probability
Regular_conditional_probability
Aspect of learning procedure
Classical conditioning (also respondent conditioning and Pavlovian conditioning) is a behavioral procedure in which a biologically potent stimulus (e
Classical_conditioning
Overview of and topical guide to probability
Independence (probability theory) The Borel–Cantelli lemmas and Kolmogorov's zero–one law Conditional probability Conditioning (probability) Conditional
Outline_of_probability
Probability theory and statistics concept
In probability theory and statistics, the conditional probability distribution is a probability distribution that describes the probability of an outcome
Conditional probability distribution
Conditional_probability_distribution
Interpretation of probability
Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is an interpretation of the concept of probability, in which, instead of frequency or
Bayesian_probability
Type of associative learning process for behavioral modification
Operant conditioning, also called instrumental conditioning, is a learning process in which voluntary behaviors are modified by association with the addition
Operant_conditioning
lemma Wick product Conditioning (probability) Conditional expectation Conditional probability distribution Regular conditional probability Disintegration
List_of_probability_topics
Hypothesis in epistemological philosophy
under radical probabilism and called it probability kinematics. Others have named it Jeffrey conditioning. Probability kinematics is not the only sufficient
Radical_probabilism
Number measuring the chance an event occurs
Probability concerns events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger
Probability
Probabilities of the presence of a condition
probability and post-test probability (alternatively spelled pretest and posttest probability) are the probabilities of the presence of a condition (such
Pre- and post-test probability
Pre-_and_post-test_probability
Determining the probability of future events based on past events
Inductive probability attempts to give the probability of future events based on past events. It is the basis for inductive reasoning, and gives the mathematical
Inductive_probability
Concept in probability theory
In probability theory, the law (or formula) of total probability is a fundamental rule relating marginal probabilities to conditional probabilities. It
Law_of_total_probability
Mathematical concept
In probability theory, a probability space or a probability triple ( Ω , F , P ) {\displaystyle (\Omega ,{\mathcal {F}},P)} is a mathematical construct
Probability_space
Expected value of a random variable given that certain conditions are known to occur
Y = y ) = 0 {\displaystyle P(Y=y)=0} . Conditioning on a discrete random variable is the same as conditioning on the corresponding event: E ( X ∣ Y
Conditional_expectation
Table in statistics
of information gives us this table of conditional probabilities for y: With more than one conditioning variable, the table would still have one row for
Conditional_probability_table
American logician
radical probabilism and the associated heuristic of probability kinematics, also known as Jeffrey conditioning. Born in Boston, Massachusetts, Jeffrey served
Richard_Jeffrey
{\displaystyle P} -functions will not be closed under conditioning, the operation that turns probability function P {\displaystyle P} into new function P C
Lewis's_triviality_result
Mathematical rule for inverting probabilities
conditional probabilities, allowing the probability of a cause to be found given its effect. For example, with Bayes' theorem, the probability that a patient
Bayes'_theorem
Random process independent of past history
In probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability
Markov_chain
Discrete probability distribution
In probability theory and statistics, the Poisson distribution (/ˈpwɑːsɒn/) is a discrete probability distribution that expresses the probability of a
Poisson_distribution
British statistician (c. 1701 – 1761)
core of almost every modern estimation approach that includes conditioned probabilities, such as sequential estimation, probabilistic machine learning
Thomas_Bayes
When the occurrence of one event does not affect the likelihood of another
Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically
Independence (probability theory)
Independence_(probability_theory)
Theorem from probability theory
In probability theory, Lindeberg's condition is a sufficient condition (and under certain conditions also a necessary condition) for the central limit
Lindeberg's_condition
Distribution of an uncertain quantity
A prior probability distribution (often simply called the prior probability, prior distribution, or prior) of an uncertain quantity is its assumed probability
Prior_probability
Tendency to misinterpret statistical experiments involving conditional probabilities
endogenous selection bias or Berkson's fallacy, is a result in conditional probability and statistics which is often found to be counterintuitive, and hence
Berkson's_paradox
Conditional probability used in Bayesian statistics
The posterior probability is a type of conditional probability that results from updating the prior probability with information summarized by the likelihood
Posterior_probability
Method of analysis of a patient's history and physical examination
diagnosis by epidemiology aims to estimate the probability of each candidate condition by comparing their probabilities to have occurred in the first place in
Differential_diagnosis
Topic in probability
the relationship between probabilities conditioned on a specified event and time-average probabilities. A Palm probability or Palm expectation, often
Palm_calculus
Statistical measure of a binary classification
the probability of a positive test result, conditioned on the individual truly being positive. Specificity (true negative rate) is the probability of a
Sensitivity_and_specificity
Model in probability theory
In probability theory, a martingale is a stochastic process in which the expected value of the next observation, given all prior observations, is equal
Martingale (probability theory)
Martingale_(probability_theory)
Notions of probabilistic convergence, applied to estimation and asymptotic analysis
In probability theory, there exist several different notions of convergence of sequences of random variables, including convergence in probability, convergence
Convergence of random variables
Convergence_of_random_variables
Probability distribution
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance
Exponential_distribution
Fundamental theorem in probability theory and statistics
In probability theory, the central limit theorem (CLT) states that, under appropriate conditions, the distribution of a normalized version of the sample
Central_limit_theorem
Complex number whose squared absolute value is a probability
In quantum mechanics, a probability amplitude is a complex number used for describing the behaviour of systems. The square modulus of this quantity at
Probability_amplitude
Consequence affecting an organism's future behavior
Reinforcement is a basic term in operant conditioning. For the punishment aspect of operant conditioning, see punishment (psychology). Positive reinforcement
Reinforcement
Statement in probability theory
conditional expectation in probability theory, where it allows replacement of the conditioning on a random variable by conditioning on the σ {\displaystyle
Doob–Dynkin_lemma
Possible result of an experiment or trial
In probability theory, an outcome is a possible result of an experiment or trial. Each possible outcome of a particular experiment is a unique random
Outcome_(probability)
Likelihood ratios used for assessing the value of performing a diagnostic test
single metric that indicates how much a test result shifts the probability that a condition (such as a disease) is present. The first description of the
Likelihood ratios in diagnostic testing
Likelihood_ratios_in_diagnostic_testing
of directed information is causal conditioning. The probability of x n {\displaystyle x^{n}} causally conditioned on y n {\displaystyle y^{n}} is defined
Directed_information
Technique for the generative modeling of a continuous probability distribution
{\mathcal {N}}(x|\mu ,\Sigma )} is the probability density at x {\displaystyle x} . A vertical bar denotes conditioning. A forward diffusion process starts
Diffusion_model
Matrix used to describe the transitions of a Markov chain
entries is a nonnegative real number representing a probability. It is also called a probability matrix, transition matrix, substitution matrix, or Markov
Stochastic_matrix
Condition in probability theory for stochastic processes
In probability theory, Novikov's condition is the sufficient condition for a stochastic process which takes the form of the Radon–Nikodym derivative in
Novikov's_condition
Collection of random variables
Chaumont; Marc Yor (2012). Exercises in Probability: A Guided Tour from Measure Theory to Random Processes, Via Conditioning. Cambridge University Press. p. 175
Stochastic_process
Probability distribution
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1)
Beta_distribution
Statistical measures of whether a finding is likely to be true
a post-test probability refers to a probability for an individual. Still, if the individual's pre-test probability of the target condition is the same
Positive and negative predictive values
Positive_and_negative_predictive_values
predictive power is a random variable since it is a conditional probability conditioned on randomly observed data. Both conditional power and predictive
Probability_of_success
Fourier transform of the probability density function
In probability theory and statistics, the characteristic function of any real-valued random variable completely defines its probability distribution. If
Characteristic function (probability theory)
Characteristic_function_(probability_theory)
Value for the flow of probability in quantum mechanics
mechanics, the probability current (sometimes called probability flux) is a mathematical quantity describing the flow of probability. Specifically, if
Probability_current
Probability puzzle
The Monty Hall problem is a brain teaser, in the form of a probability puzzle, based nominally on the American television game show Let's Make a Deal
Monty_Hall_problem
Term pioneered by B.F. Skinner
that stimulus is a negative punisher. Instrumental conditioning is another term for operant conditioning that is most closely associated with scientists
Radical_behaviorism
Process of acquiring new knowledge
learning may occur as a result of habituation, or classical conditioning, operant conditioning or as a result of more complex activities such as play, seen
Learning
Concept in psychology
improbable events, relative to events of moderate probability. Underweighting of moderate and high probabilities relative to sure things contributes to risk
Risk_aversion_(psychology)
Conceptual model in philosophy of science
same independence conditions. Conditioning on a variable is a mechanism for conducting hypothetical experiments. Conditioning on a variable involves analyzing
Causal_model
property in the probability sum theorem. When the integrand is an arbitrary function, they further establish a sufficient condition for the determinacy
Carleman's_condition
Probability of survival beyond any specified time
integral of the probability density function f(t). For the air-conditioning example, the graph of the CDF below illustrates that the probability that the time
Survival_function
Terms to describe a conditional relationship between two statements
necessary condition is one (possibly one of several conditions) that must be present in order for another condition to occur, while a sufficient condition is
Necessity_and_sufficiency
Failure analysis system used in safety engineering and reliability engineering
specified by a conditioning event. Inhibit gate – the output occurs if the input occurs under an enabling condition specified by a conditioning event. Transfer
Fault_tree_analysis
Probability estimate
In probability theory and statistics, the empirical probability or experimental probability of an event is an estimate of the probability of the event
Empirical_probability
Function related to statistics and probability theory
calculating the probability of seeing that data under different parameter values of the model. It is constructed from the joint probability distribution
Likelihood_function
Interpretation of probability
The propensity theory of probability is a probability interpretation in which the probability is thought of as a physical propensity, disposition, or tendency
Propensity_probability
Statistical significance test
the overlap between the two lists. Derivation We set up the following probability model underlying Fisher's exact test. Suppose we have a + b {\textstyle
Fisher's_exact_test
Probability distribution
In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued
Normal_distribution
Set of all possible outcomes or results of a statistical trial or experiment
In probability theory, the sample space (also called sample description space, possibility space, or outcome space) of an experiment or random trial is
Sample_space
Statistical Markov model
of a high-dimensional vector, is used as a conditioning variable of the HMM state transition probabilities. Under such a setup, eventually is obtained
Hidden_Markov_model
Method of statistical inference
closely related to subjective probability, often called "Bayesian probability". Bayesian inference derives the posterior probability as a consequence of two
Bayesian_inference
Mathematical problem involving optimal stopping theory
stopping theory that is studied extensively in the fields of applied probability, statistics, and decision theory. It is also known as the marriage problem
Secretary_problem
Quantitative measurement of accuracy
all the people that actually are positive (Condition Positive, CP = TP + FN). It can be seen as the probability that the test is positive given that the
Evaluation of binary classifiers
Evaluation_of_binary_classifiers
Ease of maintaining a functioning product or service
or product that determines the probability that it can be retained in, or restored to, a specified operating condition within a given time when maintenance
Maintainability
In probability theory, a rule for assigning epistemic probabilities
principle of insufficient reason) is a rule for assigning epistemic probabilities. The principle of indifference states that in the absence of any relevant
Principle_of_indifference
Types of error in data reporting
outcomes with the test, i.e., the conditional probability of a negative test result given that the condition being looked for is present. In statistical
False positives and false negatives
False_positives_and_false_negatives
Method of estimating the parameters of a statistical model, given observations
estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing
Maximum_likelihood_estimation
Stability of soil or rock slopes
intervention (slope stabilization) to increase the safety factor and reduce the probability of a slope movement. A previously stable slope can be affected by a number
Slope_stability
Pattern-recognition performance metrics
perform. A no-skill classifier is defined by the property that the joint probability P ( C = P , C ^ = P ) = P ( C = P ) P ( C ^ = P ) {\displaystyle \mathbb
Precision_and_recall
Conditional probability paradox
treated as conditioning on an event of probability zero, as explained in Conditional probability#Conditioning on an event of probability zero. Disintegration
Borel–Kolmogorov_paradox
conditions are equivalent. This is related to the Markov condition, an assumption made in Bayesian probability theory, that every node in a Bayesian network is
Causal_Markov_condition
Type of probability distribution
In probability theory, a probability distribution is infinitely divisible if it can be expressed as the probability distribution of the sum of an arbitrary
Infinite divisibility (probability)
Infinite_divisibility_(probability)
Notion of convergence of random variables
Uniform convergence in probability is a form of convergence in probability in statistical asymptotic theory and probability theory. It means that, under
Uniform convergence in probability
Uniform_convergence_in_probability
Paradox in probability theory
The boy or girl paradox surrounds a set of questions in probability theory, which are also known as the two children problem, Mr. Smith's children and
Boy_or_girl_paradox
Property of measure-preserving dynamical systems
an invariant probability measure is ergodic if it cannot be decomposed into a nontrivial convex combination of other invariant probability measures. Ergodic
Ergodicity
Randomly determined process
Yor (19 July 2012). Exercises in Probability: A Guided Tour from Measure Theory to Random Processes, Via Conditioning. Cambridge University Press. p. 175
Stochastic
Mathematical problem
exhaustive and exclusive for one trial (and thus their probabilities must add to 1), the probability of each is then 1/3 by the previous two steps in the
Sleeping_Beauty_problem
Range to estimate an unknown parameter
confidence level, typically 95%. A 95% confidence level does not imply a 95% probability that the true parameter lies within a particular calculated interval
Confidence_interval
Derivation of the laws of probability theory
laws of probability theory from a certain set of postulates. This derivation justifies the so-called "logical" interpretation of probability, as the laws
Cox's_theorem
statistics and probability is a list of definitions of terms and concepts used in the mathematical sciences of statistics and probability, their sub-disciplines
Glossary of probability and statistics
Glossary_of_probability_and_statistics
Stochastic point process in mathematics
mathematics, a determinantal point process is a stochastic point process, the probability distribution of which is characterized as a determinant of some function
Determinantal_point_process
Variance of a random variable given value of other variables
Mixed model Random effects model Spanos, Aris (1999). "Conditioning and regression". Probability Theory and Statistical Inference. New York: Cambridge
Conditional_variance
relational model Probability Probability bounds analysis Probability box Probability density function Probability distribution Probability distribution function
List_of_statistics_articles
Inc.) Joel Marks; cast: Thomas E. Cronin c-16m 1990 Modern President Probability and Its Uses Evan M. Maletsky c-14m April 21, 1973 Propaganda Techniques
List_of_Coronet_Films_films
lists articles related to probability theory. In particular, it lists many articles corresponding to specific probability distributions. Such articles
Catalog of articles in probability theory
Catalog_of_articles_in_probability_theory
Monte Carlo algorithm
Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult. New samples are
Metropolis–Hastings_algorithm
Measure of the accuracy of probabilistic predictions
as applied to predicted probabilities. The Brier score is applicable to tasks in which predictions must assign probabilities to a set of mutually exclusive
Brier_score
Formula in probability theory
In probability theory, the law of total covariance, covariance decomposition formula, or conditional covariance formula states that if X, Y, and Z are
Law_of_total_covariance
Value that appears most often in a set of data
is a discrete random variable, the mode is the value x at which the probability mass function P(X) takes its maximum value, i.e., x = argmaxxi P(X =
Mode_(statistics)
Probability theory concept
conditional probability, as a special case where the probability of the hypothesis given the uninformative observation is equal to the probability without
Conditional_independence
Variable that is causally influenced by two or more variables
an unconditional association between the variables that determine it. Conditioning on the collider via regression analysis, stratification, experimental
Collider_(statistics)
Uniform distribution on an interval
In probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions
Continuous uniform distribution
Continuous_uniform_distribution
Sneezing in response to numerous stimuli
reflexes. The reflection of the sun in surrounding water has a high probability of producing at least one photic sneeze for pilots who have the reflex
Photic_sneeze_reflex
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
Surname or Lastname
English
English : in all probability an English variant of Scottish Lachlan (see McLachlan), altered through folk etymology. However, Black cites one John sine terra (c. 1180–1214), suggesting that the surname could have arisen quite literally as a nickname for a man with no land.
Surname or Lastname
English (Yorkshire)
English (Yorkshire) : in all probability from the Swale river in Yorkshire. (Reaney and Wilson list a 17th-century example, Swayles, with this origin.) Alternatively, it may be a metronymic from the Old Norse female personal name Svala.
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
Surname or Lastname
English (Devon)
English (Devon) : occupational name for a toll collector, from Middle English toll ‘tax’, ‘payment’ (see Toller) + man ‘man’.
Boy/Male
Teutonic American German
Of the people.
Girl/Female
Indian
Noble, Excellent, Generous, Distinguished
Boy/Male
Tamil
Bhavyaraj | பவà¯à®¯à®°à®¾à®œ
Grand, Splendid, Goddess Parvati
Girl/Female
Indian
Boy/Male
Hindu
Skilfull and efficient Lord
Boy/Male
Hindu, Indian
Show; Who is Attaining Diksha (Knowledge)
Surname or Lastname
North German (Rudmann) and Dutch
North German (Rudmann) and Dutch : variant of Rothman(n) (see Rothman).English : nickname for a person with red hair or a ruddy complexion, from Middle English rudde ‘red’, ‘ruddy’ (see Rudd 1) + man ‘man’.Jewish (eastern Ashkenazic) : metronymic from the Yiddish female personal name Rude (variant of Rode used in Poland and Ukraine; compare Ratkovich) + Yiddish man ‘man’, in the sense ‘husband’.
Girl/Female
Muslim/Islamic
Successful and victorious
Girl/Female
Hindu, Indian
Treasure
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
CONDITIONING PROBABILITY
n.
The quality or state of being verisimilar; the appearance of truth; probability; likelihood.
n.
The quality or state of being probable; appearance of reality or truth; reasonable ground of presumption; likelihood.
a.
Having probability; having or giving reason to expect; -- followed by the infinitive; as, it is likely to rain.
v. t.
To take or suppose to be true, or entitled to belief, without examination or proof, or on the strength of probability; to take for granted; to infer; to suppose.
n.
Ground for presuming; evidence probable, but not conclusive; strong probability; reasonable supposition; as, the presumption is that an event has taken place.
p. pr. & vb. n.
of Condition
a.
Difference in favor of one and against another; excess of one of two things or numbers over the other; inequality; advantage; superiority; hence, excess of chances; probability.
n.
Likelihood; probability.
n.
Appearance of truth or reality; probability; verisimilitude.
n.
Probability.
adv.
In all probability; probably.
n.
That which is or appears probable; anything that has the appearance of reality or truth.
superl.
Having probability; affording probability; probable; likely.
adv.
By presumption, or supposition grounded or probability; presumably.
n.
One who maintains that certainty is impossible, and that probability alone is to govern our faith and actions.
adv.
In a manner calculated to serve as the basis of action; according to the usual course of things and human judgment; according to reason and probability.
n.
One who maintains that a man may do that which has a probability of being right, or which is inculcated by teachers of authority, although other opinions may seem to him still more probable.
n.
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, n., 5.
pl.
of Probability
a.
Based on presumption or probability; grounded on probable evidence; probable; as, presumptive proof.