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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
Probability of an event occurring, given that another event has already occurred
In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption
Conditional_probability
Type of probability distribution
other variables, and the conditional probability distribution giving the probabilities for any subset of the variables conditional on particular values of
Joint probability distribution
Joint_probability_distribution
Aspect of probability and statistics
of the other variables. This contrasts with a conditional distribution, which gives the probabilities contingent upon the values of the other variables
Marginal_distribution
Concept in probability theory
of a random variable. The resulting conditional probability distribution is a parametrized family of probability measures called a Markov kernel. Consider
Regular conditional probability
Regular_conditional_probability
Expected value of a random variable given that certain conditions are known to occur
variable is its expected value evaluated with respect to the conditional probability distribution. If the random variable can take on only a finite number
Conditional_expectation
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
Probability theory concept
conditional dependence. Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of
Conditional_independence
field Conditional random field Borel–Cantelli lemma Wick product Conditioning (probability) Conditional expectation Conditional probability distribution Regular
List_of_probability_topics
Mathematical model used for classification or regression
conditional models, are a class of models frequently used for classification. In machine learning, it typically models the conditional distribution P(Y∣X)
Discriminative_model
Concept in statistics
of the parametrized distribution ("conditional distribution"). A compound probability distribution is the probability distribution that results from assuming
Compound probability distribution
Compound_probability_distribution
Many probability distributions that are important in theory or applications have been given specific names. The Bernoulli distribution, which takes value
List of probability distributions
List_of_probability_distributions
Mathematical function for the probability a given outcome occurs in an experiment
In probability theory and statistics, a probability distribution describes how probabilities are assigned to the possible results of a random phenomenon—more
Probability_distribution
Distributions in probability theory
In probability theory and statistics, the Dirichlet-multinomial distribution is a family of discrete multivariate probability distributions on a finite
Dirichlet-multinomial distribution
Dirichlet-multinomial_distribution
Probability distribution
The Pareto distribution, named after the Italian polymath Vilfredo Pareto, is a probability distribution in the form of a power law that is used to describe
Pareto_distribution
Conditional independence of exchangeable observations
i.d. sequences. A Bayesian statistician often seeks the conditional probability distribution of a random quantity given the data. The concept of exchangeability
De_Finetti's_theorem
Conditional Poisson distribution restricted to positive integers
This distribution is also known as the conditional Poisson distribution or the positive Poisson distribution. It is the conditional probability distribution
Zero-truncated Poisson distribution
Zero-truncated_Poisson_distribution
Overview of and topical guide to probability
The axioms of probability Boole's inequality Probability interpretations Bayesian probability Frequency probability Conditional probability The law of total
Outline_of_probability
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
Table in statistics
the conditional probability table (CPT) is defined for a set of discrete and mutually dependent random variables to display conditional probabilities of
Conditional_probability_table
Probability distribution
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance
Exponential_distribution
Variance of a random variable given value of other variables
In probability theory and statistics, a conditional variance is the variance of a random variable given the value(s) of one or more other variables. Particularly
Conditional_variance
Probability theory term
formalized in probability theory by conditioning. Conditional probabilities, conditional expectations, and conditional probability distributions are treated
Conditioning_(probability)
Probability theory concept
the joint distribution of random variables respectively, using conditional probabilities. This rule allows one to express a joint probability in terms
Chain_rule_(probability)
Random process independent of past history
of these to states. The Markov property states that the conditional probability distribution for the system at the next step (and in fact at all future
Markov_chain
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
Measure for evaluating probabilistic forecasts
multivariate distribution D {\displaystyle D} by evaluation of CRPS over a prescribed set of univariate conditional probability distributions of the predicted
Scoring_rule
mathematical notation, conditional probability is written P(A|B), and is read "the probability of A, given B". conditional probability distribution confidence interval
Glossary of probability and statistics
Glossary_of_probability_and_statistics
Problem asking the probability that the sun will rise tomorrow
rule. Having found the conditional probability distribution of p given the data, one may then calculate the conditional probability, given the data, that
Sunrise_problem
Waiting time property of certain probability distributions
In probability and statistics, memorylessness is a property of probability distributions. It describes situations where previous failures or elapsed time
Memorylessness
Probability distribution
In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes
Binomial_distribution
Probability distribution
probability theory and statistics, the geometric distribution is either one of two discrete probability distributions: The probability distribution of
Geometric_distribution
Probability distribution
probability theory and statistics, Student's t distribution (or simply the t distribution) t ν {\displaystyle t_{\nu }} is a continuous probability distribution
Student's_t-distribution
Mathematical rule for inverting probabilities
inverting conditional probabilities, allowing the probability of a cause to be found given its effect. For example, with Bayes' theorem, the probability that
Bayes'_theorem
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
Distribution of an uncertain quantity
with new information to obtain the posterior probability distribution, which is the conditional distribution of the uncertain quantity given new data. Historically
Prior_probability
Probability distribution
In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally
Log-normal_distribution
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
Particular case of the generalized extreme value distribution
In probability theory and statistics, the Gumbel distribution (also known as the type-I generalized extreme value distribution) is used to model the distribution
Gumbel_distribution
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
Stochastic process in physics
continuous-time gaussian process B(t) whose probability distribution is the conditional probability distribution of a standard Wiener process W(t) (a mathematical
Brownian_bridge
In mathematics and computer science, the method of conditional probabilities is a systematic method for converting non-constructive probabilistic existence
Method of conditional probabilities
Method_of_conditional_probabilities
Statistical modeling technique
th conditional quantile of Y {\displaystyle Y} given X {\displaystyle X} is the τ {\displaystyle \tau } th quantile of the Conditional probability distribution
Quantile_regression
Conditional distribution in statistics
distribution is a conditional distribution that results from restricting the domain of some other probability distribution. Truncated distributions arise
Truncated_distribution
Statistical modeling method
the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution
Linear_regression
Family of continuous probability distributions
In probability and statistics, the skewed generalized "t" distribution is a family of continuous probability distributions. The distribution was first
Skewed generalized t distribution
Skewed_generalized_t_distribution
Compound probability distribution
Poisson distribution is a univariate discrete probability distribution in stochastics. It results from assuming that the conditional distribution of a random
Mixed_Poisson_distribution
When the occurrence of one event does not affect the likelihood of another
often is also used for conditional independence) if and only if their joint probability equals the product of their probabilities: A ∩ B ≠ ∅ {\displaystyle
Independence (probability theory)
Independence_(probability_theory)
Statistical Markov model
trellis diagram) denote conditional dependencies. From the diagram, it is clear that the conditional probability distribution of the hidden variable x(t)
Hidden_Markov_model
1763 mathematics essay by Thomas Bayes
is the conditional probability distribution of p, given the numbers of successes and failures so far observed. The answer is that its probability density
An Essay Towards Solving a Problem in the Doctrine of Chances
An_Essay_Towards_Solving_a_Problem_in_the_Doctrine_of_Chances
Topics referred to by the same term
automaton a stochastic kernel In statistics and probability theory, the conditional probability distribution function controlling the transitions of a stochastic
Transition_function
Distribution of new data marginalized over the posterior
statistics, the posterior predictive distribution is the distribution of possible unobserved values conditional on the observed values. Given a set of
Posterior predictive distribution
Posterior_predictive_distribution
Discrete probability distribution
In probability theory and statistics, a categorical distribution (also called a generalized Bernoulli distribution, multinoulli distribution) is a discrete
Categorical_distribution
British statistician (c. 1701 – 1761)
conditionally independent given the value of R. Then the conditional probability distribution of R, given the values of X1, ..., Xn, is ( n + 1 ) ! S
Thomas_Bayes
making. The probability of success is a concept closely related to conditional power and predictive power. Conditional power is the probability of observing
Probability_of_success
Paradigm in machine learning that uses no classification labels
infer a conditional probability distribution conditioned on the label of input data; unsupervised learning intends to infer an a priori probability distribution
Unsupervised_learning
Probability distribution
In probability and statistics, the Dirichlet distribution (after Peter Gustav Lejeune Dirichlet), often denoted Dir ( α ) {\displaystyle \operatorname
Dirichlet_distribution
Generalization of the one-dimensional normal distribution to higher dimensions
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization
Multivariate normal distribution
Multivariate_normal_distribution
Probability distribution
The Cauchy distribution, named after Augustin-Louis Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as
Cauchy_distribution
Concept in statistics
statistics, the concept of the shape of a probability distribution arises in questions of finding an appropriate distribution to use to model the statistical properties
Shape of a probability distribution
Shape_of_a_probability_distribution
expectation Conditional independence Conditional probability Conditional probability distribution Conditional random field Conditional variance Conditionality principle
List_of_statistics_articles
Technique for the generative modeling of a continuous probability distribution
_{t}p_{t}+\nabla \cdot (v_{t}p_{t})=0} To construct a probability path, we start by construct a conditional probability path p t ( x | z ) {\displaystyle p_{t}(x\vert
Diffusion_model
Scientific study of digital information
done by comparing the conditional and unconditional distributions. The former quantity is a property of the probability distribution of a random variable
Information_theory
Information-theoretical limit on transmission rate in a communication channel
p(y|x)=p_{Y|X}(y|x)} is the noisy channel, which is modeled by a conditional probability distribution; and, g n {\displaystyle g_{n}} is the decoding function
Channel_capacity
Statistical principle
is sufficient for underlying parameter θ precisely if the conditional probability distribution of the data X, given the statistic t = T(X), does not depend
Sufficient_statistic
Probability theory paradox
equations describing the invariances to directly determine the probability distribution. These integral equations indeed have a unique solution, and it
Bertrand paradox (probability)
Bertrand_paradox_(probability)
Machine learning paradigm
find g {\displaystyle g} . When g {\displaystyle g} is a conditional probability distribution P ( y | x ) {\displaystyle P(y|x)} and the loss function
Supervised_learning
Generalization of the binomial distribution
In probability theory, the multinomial distribution is a generalization of the binomial distribution. For example, it models the probability of counts
Multinomial_distribution
Topics referred to by the same term
pulmonary disease, a pathological condition Conditional probability distribution, a kind of distribution in statistics Copy/Paste Detector, software to
CPD
Probability distribution
In probability theory and statistics, the gamma distribution is a versatile two-parameter family of continuous probability distributions. The exponential
Gamma_distribution
Probability of shared birthdays
birthday, which occurs with probability 1. This conjunction of events may be computed using conditional probability: the probability of Event 2 is 364/365
Birthday_problem
Information theory
In probability theory, particularly information theory, the conditional mutual information is, in its most basic form, the expected value of the mutual
Conditional mutual information
Conditional_mutual_information
Model for generating observable data in probability and statistics
estimate the joint distribution P ( X , Y ) {\displaystyle P(X,Y)} (generative model), from that compute the conditional probability P ( Y | X = x ) {\displaystyle
Generative_model
Average uncertainty in variable's states
needed to describe the state of the variable, considering the distribution of probabilities across all potential states. Given a discrete random variable
Entropy_(information_theory)
Random variable with multiple component dimensions
distributions. The conditional probability distribution of X i {\displaystyle X_{i}} given X j {\displaystyle X_{j}} is the probability distribution of
Multivariate_random_variable
Graphical model
an RDN can learn the parameters independently, with the conditional probability distributions estimated separately. Since there may be some inconsistencies
Relational_dependency_network
Monte Carlo algorithm
multivariate probability distribution when direct sampling from the joint distribution is difficult, but sampling from the conditional distribution is more
Gibbs_sampling
Probability puzzle
open by the host. Many probability text books and articles in the field of probability theory derive the conditional probability solution through a formal
Monty_Hall_problem
Theorem in measure theory
the measure space in question. It is related to the existence of conditional probability measures. In a sense, "disintegration" is the opposite process
Disintegration_theorem
Statistical model for a binary dependent variable
categorical outcome y will be in category y=n, conditional on the vector of covariates x. The sum of these probabilities over all categories must equal 1. Using
Logistic_regression
Concept in science
quasiprobability for some events. These distributions may apply to unobservable events or conditional probabilities. In 1942, Paul Dirac wrote a paper "The
Negative_probability
Probabilistic graphical representation of causal relationships
represent the joint probability distribution, it is necessary to specify for each node X the probability distribution for X conditional upon X's parents
Bayesian_network
Class of statistical models
as an event tree or probability tree). A staged tree places equality relationships on the conditional probability distributions of an event tree. These
Staged_tree_(mathematics)
and fluctuations in financial markets. A formula for the conditional probability distribution of the extremum of the Wiener process and a sketch of its
Probability distribution of extreme points of a Wiener stochastic process
Probability_distribution_of_extreme_points_of_a_Wiener_stochastic_process
Number measuring the chance an event occurs
of events. Conditional probability is the probability of some event A, given the occurrence of some other event B. Conditional probability is written
Probability
Probability distribution
In probability theory and statistics, the skew normal distribution is a continuous probability distribution that generalises the normal distribution to
Skew_normal_distribution
Family of distributions that generalize the multivariate normal distribution
In probability and statistics, an elliptical distribution is any member of a broad family of probability distributions that generalize the multivariate
Elliptical_distribution
Probability distribution modeling a coin toss which need not be fair
In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete probability distribution
Bernoulli_distribution
Problem in statistical estimation
N=n,K=1)=(m\mid n)={\frac {[m\leq n]}{n}}} This is the conditional probability mass distribution function of m {\displaystyle m} . When considered a function
German_tank_problem
Probability distribution that has the most entropy of a class
entropy probability distribution has entropy that is at least as great as that of all other members of a specified class of probability distributions. According
Maximum entropy probability distribution
Maximum_entropy_probability_distribution
Stochastic process generalizing Brownian motion
calculate the conditional probability distribution of the maximum in interval [ 0 , t ] {\textstyle [0,t]} (cf. Probability distribution of extreme points
Wiener_process
Measure of the asymmetry of random variables
Skewness in probability theory and statistics is a measure of the asymmetry of the probability distribution of a real-valued random variable about its
Skewness
Overview of and topical guide to statistics
learning Probability distribution Symmetric probability distribution Unimodal probability distribution Conditional probability distribution Probability density
Outline_of_statistics
Measure of total value one, generalizing probability distributions
{\displaystyle 1/4+1/2=3/4,} as in the diagram on the right. The conditional probability based on the intersection of events defined as: μ ( B ∣ A ) = μ
Probability_measure
Heavy-tail probability distribution
The Lomax distribution, conditionally also called the Pareto Type II distribution, is a heavy-tail probability distribution used in business, economics
Lomax_distribution
Class of algorithms in information theory
{\mathcal {X}},{\mathcal {Y}}} , and a channel law as a conditional probability distribution p ( y | x ) {\displaystyle p(y|x)} . The channel capacity
Blahut–Arimoto_algorithm
Class of nonparametric methods
embedding of distributions (also called the kernel mean or mean map) comprises a class of nonparametric methods in which a probability distribution is represented
Kernel embedding of distributions
Kernel_embedding_of_distributions
Type of probability distribution
Then X {\displaystyle X} conditional on a < X < b {\displaystyle a<X<b} has a truncated normal distribution. Its probability density function, f {\displaystyle
Truncated_normal_distribution
Method of statistical inference
available. Fundamentally, Bayesian inference uses a prior distribution to estimate posterior probabilities. Bayesian inference is an important technique in statistics
Bayesian_inference
Fourth standardized moment in statistics
refers to the degree of tailedness in the probability distribution of a real-valued, random variable in probability theory and statistics. Similar to skewness
Kurtosis
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
Surname or Lastname
English
English : habitational name from either of two places in Devon named Hunnacott, from either the Old English personal name HunÄ or Old English hunig ‘honey’ + cot ‘cottage’. There is also a place named Huncoat in Lancashire, which has the same origin, but the distribution of the surname in England suggests that it probably did not contribute to the surname.
Boy/Male
Tamil
Can travel in all climatic conditions
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.
Girl/Female
Tamil
Good or Happy condition, Solution, Fortune
Girl/Female
Hindu
Good or Happy condition, Solution
Boy/Male
Indian
Can Travel in All Climatic Conditions
Surname or Lastname
English
English : habitational name from a place in Devon, recorded in Domesday Book as Loba, apparently a topographical term meaning perhaps ‘lump’, ‘hill’, the village being situated at the bottom of a hill. There is also a place of the same name in Oxfordshire (recorded in 1208 as Lobbe), but the historical and contemporary distribution of the surname (which is still largely restricted to Devon), makes it unlikely that it ever derived from this place, or from Middle English, Old English lobbe ‘spider’.
Surname or Lastname
English
English : habitational name from places so called in North Yorkshire, Hampshire, and Kent. The Yorkshire place is named from the Old English personal name Hūna + tūn ‘enclosure’, ‘settlement’; that in Hampshire from the genitive plural of hund ‘hound’ + tūn ‘enclosure’, ‘settlement’; and the Kentish place from Old English huntena, genitive plural of hunta ‘hunter’ + dūn ‘hill’. The present-day distribution shows clusters in North and South Yorkshire, and also in Norfolk.
Boy/Male
Arabic
State; Condition
Boy/Male
Bengali, Indian
Sleepless; Condition of Being Awake; One who Conquers Sleep
Girl/Female
Tamil
Circumstance, Period of life, Wick, Condition, Degree
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.
Girl/Female
Tamil
Good or Happy condition, Solution
Surname or Lastname
English (West Yorkshire)
English (West Yorkshire) : topographic name for someone who lived in a long valley, from Middle English long + botme, bothem ‘valley bottom’. Given the surname’s present-day distribution, Longbottom in Luddenden Foot, West Yorkshire, may be the origin, but there are also two places called Long Bottom in Hampshire, two in Wiltshire, and Longbottom Farm in Somerset and in Wiltshire.
Girl/Female
Indian
Circumstance, Period of life, Wick, Condition, Degree
Girl/Female
Hindu
Good or Happy condition, Solution, Fortune
Boy/Male
African, Arabic, Australian, Greek, Swahili
Unique; Graceful; Kind; Sweet; The Beautiful Ocean; Loving; Forgiving; Content; Delighted; Beauty; Perfect; State; Handsome; Condition; The Sea
Surname or Lastname
English
English : habitational name from the place in Bedfordshire (named in Old English as ‘settlement (Old English tūn) on the (river) Lea’), or, more plausibly in view of the pattern of distribution, from Luton in Devon (near Teignmouth), named in Old English as ‘Lēofgifu’s settlement’ (from an Old English female personal name composed of the elements lēof ‘dear’, ‘beloved’ + gifu ‘gift’). A further possible source of the name is Luton in Kent, named as the ‘settlement of Lēofa’.
Surname or Lastname
English
English : habitational name from a place named in Old English with hÄlig ‘holy’ + Old English feld ‘open country’. This may be Holyfield in Essex (which belonged to Waltham Abbey), but the present-day distribution of the name (mainly in the Midlands and Wales) suggests that another source may be involved.
Boy/Male
African, Arabic, Australian, French, Indian, Muslim, Sindhi
Sacrifice; Unconditional Love; Love
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
Boy/Male
American, Christian, Danish, Finnish, French, German, Indian, Latin, Swedish
Kyle
Boy/Male
Russian
laurel'.
Surname or Lastname
English
English : unexplained. It is said by family historians to be a variant of Questenbury, but no surname or place name of that spelling is known in Britain. It may be an altered form of Glastonbury, a habitational name from the place of this name in Somerset.American bearers of the name Christenberry are all said to be descended from Thomas Questenbury (1600–72), who came to VA in 1624 from Bromley, Kent, England.
Boy/Male
Gaelic
Son of Alasdair.
Girl/Female
Assamese, Bengali, Hindu, Indian, Kannada, Malayalam, Marathi, Sindhi, Telugu
Goddess Durga
Boy/Male
Hindu, Indian
Happy
Surname or Lastname
English
English : habitational name from a place in Greater Manchester (formerly in Cheshire) called Warburton, from the Old English female personal name Wǣrburh (composed of the elements wǣr ‘pledge’ + burh ‘fortress’) + Old English tūn ‘enclosure’, ‘settlement’.
Girl/Female
Afghan, Arabic, Iranian, Muslim, Parsi
Glory of the Moon
Girl/Female
Hindu
Saisudha, Early morning, Dawn
Girl/Female
Tamil
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
CONDITIONAL PROBABILITY-DISTRIBUTION
n.
Probability.
adv.
In a conditional manner; subject to a condition or conditions; not absolutely or positively.
a.
Containing, implying, or depending on, a condition or conditions; not absolute; made or granted on certain terms; as, a conditional promise.
superl.
Having probability; affording probability; probable; likely.
n.
To invest with, or limit by, conditions; to burden or qualify by a condition; to impose or be imposed as the condition of.
adv.
Conditionally.
a.
Unconditional.
a.
Not conditional limited, or conditioned; made without condition; absolute; unreserved; as, an unconditional surrender.
n.
Likelihood; probability.
a.
Expressing a condition or supposition; as, a conditional word, mode, or tense.
imp. & p. p.
of Condition
n.
Probability.
a.
Surrounded; circumstanced; in a certain state or condition, as of property or health; as, a well conditioned man.
v. t.
To put under conditions; to render conditional.
n.
One who maintains that certainty is impossible, and that probability alone is to govern our faith and actions.
a.
Not conditioned or subject to conditions; unconditional.
n.
A conditional word, mode, or proposition.
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.
v. t.
Conditional.
n.
The doctrine of the probabilists.