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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
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
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
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 theory concept
conditional dependence. Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of
Conditional_independence
Expected value of a random variable given that certain conditions are known to occur
In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated
Conditional_expectation
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 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
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
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
Hypothesis about sapient life and the universe
Schmidhuber, the anthropic principle essentially just says that the conditional probability of finding yourself in a universe compatible with your existence
Anthropic_principle
Concept in probability theory
In probability theory, conditional dependence is a relationship between two or more events that are dependent when a third event occurs. It is the opposite
Conditional_dependence
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
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
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)
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
Type of probability distribution
variables, and the conditional probability distribution giving the probabilities for any subset of the variables conditional on particular values of the
Joint probability distribution
Joint_probability_distribution
Measure of relative information in probability theory
Intuitively, notice that by definition of expected value and of conditional probability, H ( Y | X ) {\displaystyle \displaystyle H(Y|X)} can be written
Conditional_entropy
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
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
Probabilistic graphical representation of causal relationships
the joint probability function Pr ( G , S , R ) {\displaystyle \Pr(G,S,R)} and the conditional probabilities from the conditional probability tables (CPTs)
Bayesian_network
Diagram to represent a probability space in probability theory
series of independent events (such as a set of coin flips) or conditional probabilities (such as drawing cards from a deck, without replacing the cards)
Tree diagram (probability theory)
Tree_diagram_(probability_theory)
Family of logics for natural-language and counterfactual conditionals
logic, belief revision, conditional probability and the pragmatics of assertion, questioning and decision-making. Conditional logics form a family of
Conditional_logic
Mathematical model used for classification or regression
regression (LR), conditional random fields (CRFs), decision trees among many others. Unlike generative modelling, which studies the joint probability P ( x , y
Discriminative_model
Probability theory concept
respectively, using conditional probabilities. This rule allows one to express a joint probability in terms of only conditional probabilities. The rule is notably
Chain_rule_(probability)
Random process independent of past history
mapping 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
Markov_chain
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
Conditional probability paradox
In probability theory, the Borel–Kolmogorov paradox (sometimes known as Borel's paradox) is a paradox relating to conditional probability with respect
Borel–Kolmogorov_paradox
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
Model for generating observable data in probability and statistics
(computing one conditional probability in terms of the other) and the definition of conditional probability (computing conditional probability in terms of
Generative_model
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)
probability (so that the step can remain randomized) or one derandomizes the rounding step, typically using the method of conditional probabilities.
Randomized_rounding
Probability theory term
is formalized in probability theory by conditioning. Conditional probabilities, conditional expectations, and conditional probability distributions are
Conditioning_(probability)
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
Foundations of probability theory
The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. Like all axiomatic
Probability_axioms
Theory and paradigm of statistics
theorem to compute and update probabilities after obtaining new data. Bayes' theorem describes the conditional probability of an event based on data as
Bayesian_statistics
Topics referred to by the same term
Y Conditional probability, the probability of an event A given that another event B Conditional proof, in logic: a proof that asserts a conditional, and
Conditional
mathematical notation, conditional probability is written P(A|B), and is read "the probability of A, given B". conditional probability distribution confidence
Glossary of probability and statistics
Glossary_of_probability_and_statistics
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
Concept in science
events. These distributions may apply to unobservable events or conditional probabilities. In 1942, Paul Dirac wrote a paper "The Physical Interpretation
Negative_probability
Statistical significance test
balls. Finally, we compute that conditional on having a + c {\textstyle a+c} class I balls, the conditional probability of having a table as shown is (
Fisher's_exact_test
Branch of actuarial mathematics
heads is the conditional probability of a heads-only coin times the probability of heads for a heads-only coin plus the conditional probability of a fair
Credibility_theory
Branch of mathematics concerning probability
Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations
Probability_theory
English scientist
perception. (He achieved a Ph.D. no later than 1946.) He was designing conditional-probability neural nets for pattern recognition for the British military. He
Albert_Uttley
Random field Conditional random field Borel–Cantelli lemma Wick product Conditioning (probability) Conditional expectation Conditional probability distribution
List_of_probability_topics
Statistic quantifying the association between two events
"cell probabilities" that sum to one. The odds for Y within the two subpopulations defined by X = 1 and X = 0 are defined in terms of the conditional probabilities
Odds_ratio
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
Statistical matching technique
introduced the technique in 1983, defining the propensity score as the conditional probability of a unit (e.g., person, classroom, school) being assigned to the
Propensity_score_matching
Probabilistic theory of knowledge
evidence. The axioms of probability and the principal principle belong to the static principles while the principle of conditionalization governs the dynamic
Bayesian_epistemology
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
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)
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
Distributions in probability theory
unnormalized conditional probability of the words, while the topic conditional probability requires the actual (i.e. normalized) probability. Hence we have
Dirichlet-multinomial distribution
Dirichlet-multinomial_distribution
In statistics and probability theory, set of outcomes to which a probability is assigned
family of subsets. For the standard tools of probability theory, such as joint and conditional probabilities, to work, it is necessary to use a σ-algebra
Event_(probability_theory)
List of statements that appear to contradict themselves
entry length on both books. Bertrand's box paradox: A paradox of conditional probability closely related to the Boy or Girl paradox. Bertrand's paradox:
List_of_paradoxes
Paradox in probability theory
second child (i.e., boy and girl), and that the probability of these outcomes is absolute, not conditional. First, it is assumed that the space of all possible
Boy_or_girl_paradox
Statistics model
{\displaystyle y^{*}>0} , and zero otherwise, and consider the conditional probability P r ( y = 1 ∣ x ) = P r ( y ∗ > 0 ∣ x ) = P r ( b 0 + x ′ b + ε
Linear_probability_model
Probabilistic classification algorithm
for classification. Abstractly, naive Bayes is a conditional probability model: it assigns probabilities p ( C k ∣ x 1 , … , x n ) {\displaystyle p(C_{k}\mid
Naive_Bayes_classifier
Average uncertainty in variable's states
property with respect to a partition of a set. Meanwhile, the conditional probability is defined in terms of a multiplicative property, P ( A ∣ B ) ⋅
Entropy_(information_theory)
Type of probability space
In probability theory, a standard probability space, also called Lebesgue–Rokhlin probability space or just Lebesgue space (the latter term is ambiguous)
Standard_probability_space
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
Scientific study of digital information
is done by comparing the conditional and unconditional distributions. The former quantity is a property of the probability distribution of a random variable
Information_theory
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
British statistician (c. 1701 – 1761)
either 1 or 0 and the conditional probability that any of them is equal to 1, given the value of R, is R. Suppose they are conditionally independent given
Thomas_Bayes
Machine learning paradigm
linear discriminant analysis are joint probability models, whereas logistic regression is a conditional probability model. There are two basic approaches
Supervised_learning
Observed value of a random variable
In probability and statistics, a realization or observation (also called observed value) of a random variable or random element is the value that is actually
Realization_(probability)
Rule of logical inference
base rate (aka. prior probability) of P {\displaystyle P} . The conditional probability Pr ( Q ∣ P ) {\displaystyle \Pr(Q\mid P)} generalizes the logical
Modus_tollens
Logical fallacy
inverse, also called the conditional probability fallacy or the inverse fallacy, is a logical fallacy whereupon a conditional probability is equated with its
Confusion_of_the_inverse
Natural-language "if" sentences about what may be the case
portal Conditional logic Counterfactual conditional Logical consequence Material conditional Strict conditional Pragmatics Conditional probability Edgington
Indicative_conditional
Method used in intelligent tutoring systems
application. The conditional probability is used to update the probability of skill mastery calculated by equation (d). To figure out the probability of the student
Bayesian_knowledge_tracing
Types of error in data reporting
all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present.
False positives and false negatives
False_positives_and_false_negatives
Procedure that can be infinitely repeated, with a well-defined set of outcomes
In probability theory, an experiment or trial (see below) is the mathematical model of any procedure that can be infinitely repeated and has a well-defined
Experiment (probability theory)
Experiment_(probability_theory)
Test for the acceptability of conditionals via hypothetical belief revision
generally for non-trivial probability functions, motivating weaker connections between conditional probability and conditional acceptability. A related
Ramsey_test
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
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
expectation Conditional independence Conditional probability Conditional probability distribution Conditional random field Conditional variance Conditionality principle
List_of_statistics_articles
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
Probability distribution
30 seconds, the conditional probability that occurrence will take at least 10 more seconds is equal to the unconditional probability of observing the
Exponential_distribution
Probabilistic primality test
instead in the inverse conditional probability Pr ( ¬ P ∣ M R k ) {\displaystyle \Pr(\lnot P\mid M\!R_{k})} : the probability that a number which has
Miller–Rabin_primality_test
Machine learning problem
Some models, such as logistic regression, are conditionally trained: they optimize the conditional probability Pr ( Y | X ) {\displaystyle \Pr(Y\vert X)}
Probabilistic_classification
Collection of random variables
In probability theory and related fields a stochastic (/stəˈkæstɪk/) or random process is a mathematical object usually defined as a family of random
Stochastic_process
Function related to statistics and probability theory
within the context of information theory. Bayes factor Conditional entropy Conditional probability Empirical likelihood Likelihood principle Likelihood-ratio
Likelihood_function
In probability theory, a conditional event algebra (CEA) is an alternative to a standard, Boolean algebra of possible events (a set of possible events
Conditional_event_algebra
Thought experiment, to justify Bayesian probability
way that parallels the simplest conventional characterization of conditional probability. In the 2015 running of the Kentucky Derby, the favorite ("American
Dutch_book_arguments
Process forming a path from many random steps
{Z} } which starts at 0, and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in
Random_walk
field E. 4. In probability theory, denotes a conditional probability. For example, P ( A / B ) {\displaystyle P(A/B)} denotes the probability of A, given
Glossary of mathematical symbols
Glossary_of_mathematical_symbols
Overview of and topical guide to statistics
learning Probability distribution Symmetric probability distribution Unimodal probability distribution Conditional probability distribution Probability density
Outline_of_statistics
of probability, Lewis's triviality result (named after David Lewis) is a theorem about the impossibility of systematically equating the conditional probability
Lewis's_triviality_result
Object detection system
{\displaystyle p_{i}} is the conditional probability that the cell contains an object of class i {\displaystyle i} , conditional on the cell containing at
You_Only_Look_Once
Statistical Markov model
called a trellis diagram) denote conditional dependencies. From the diagram, it is clear that the conditional probability distribution of the hidden variable
Hidden_Markov_model
Conditional Poisson distribution restricted to positive integers
distribution is also known as the conditional Poisson distribution or the positive Poisson distribution. It is the conditional probability distribution of a Poisson-distributed
Zero-truncated Poisson distribution
Zero-truncated_Poisson_distribution
Theorem in probability theory
fundamental result in probability theory that expresses the variance of a random variable Y in terms of its conditional variances and conditional means given another
Law_of_total_variance
How one process influences another
empirical regularities (constant conjunctions of events), changes in conditional probabilities, counterfactual conditions, mechanisms underlying causal relations
Causality
A ∣ B ) {\displaystyle \textstyle P(A\mid B)} , the conditional probability, is the probability of A {\displaystyle \textstyle A} given B {\displaystyle
Notation in probability and statistics
Notation_in_probability_and_statistics
Determining the probability of future events based on past events
turns out to be the same. Bayes' theorem is about conditional probabilities, and states the probability that event B happens if firstly event A happens:
Inductive_probability
Uniform distribution on an interval
a conditional probability case for the continuous uniform distribution: given that X > 8 {\displaystyle X>8} is true, what is the probability that
Continuous uniform distribution
Continuous_uniform_distribution
Statistical model written in multiple levels
P(\theta ,y)=P(\theta )P(y\mid \theta )} Using the basic property of conditional probability, the posterior distribution will yield: P ( θ ∣ y ) = P ( θ , y
Bayesian hierarchical modeling
Bayesian_hierarchical_modeling
new particles. The original motivation for CLs was based on a conditional probability calculation suggested by physicist G. Zech for an event counting
CLs_method_(particle_physics)
Method of statistical inference
zero, then the probability of the hypothesis, given the evidence, P ( H ∣ E ) {\displaystyle P(H\mid E)} is close to 1 or the conditional hypothesis is
Bayesian_inference
Type of language model
back-off is a generative n-gram language model that estimates the conditional probability of a word given its history in the n-gram. It accomplishes this
Katz's_back-off_model
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
Girl/Female
Hindu
Good or Happy condition, Solution
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 (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.
Boy/Male
Bengali, Indian
Sleepless; Condition of Being Awake; One who Conquers Sleep
Boy/Male
Tamil
Can travel in all climatic conditions
Boy/Male
Arabic
State; Condition
Boy/Male
African, Arabic, Australian, French, Indian, Muslim, Sindhi
Sacrifice; Unconditional Love; Love
Boy/Male
Indian
Can Travel in All Climatic Conditions
Girl/Female
Tamil
Good or Happy condition, Solution
Girl/Female
Indian
Circumstance, Period of life, Wick, Condition, Degree
Girl/Female
Tamil
Circumstance, Period of life, Wick, Condition, Degree
Girl/Female
Hindu
Good or Happy condition, Solution, Fortune
Girl/Female
Tamil
Good or Happy condition, Solution, Fortune
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.
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
Girl/Female
Bengali, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi
Evening Time
Girl/Female
Muslim/Islamic
Plenty
Boy/Male
English
Mountain Peak
Girl/Female
Yiddish
Bitter.
Boy/Male
Indian
Intelligent; Lord Balaji
Boy/Male
Indian
Blooming, Shining, Clear
Boy/Male
Hindu, Indian
Lord Shiva
Girl/Female
Arthurian Legend
Arthur's queen.
Boy/Male
American, Australian, British, Christian, English
Son; A Nickname and Given Name; Youngster
Girl/Female
British, English
Jasmine Flower
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY
adv.
Conditionally.
a.
Not conditional limited, or conditioned; made without condition; absolute; unreserved; as, an unconditional surrender.
a.
Having, or known under or by, conditions or relations; not independent; not absolute.
a.
Unconditional.
v. t.
Conditional.
v. t.
To put under conditions; to render conditional.
n.
train; acclimate.
n.
A limitation.
adv.
In a conditional manner; subject to a condition or conditions; not absolutely or positively.
n.
A conditional word, mode, or proposition.
imp. & p. p.
of Condition
v. t.
To qualify by conditions; to regulate.
n.
To invest with, or limit by, conditions; to burden or qualify by a condition; to impose or be imposed as the condition of.
a.
Surrounded; circumstanced; in a certain state or condition, as of property or health; as, a well conditioned man.
a.
Of the nature of a proviso; containing a proviso or condition; conditional; as, a provisory clause.
a.
Containing, implying, or depending on, a condition or conditions; not absolute; made or granted on certain terms; as, a conditional promise.
n.
To put under conditions; to require to pass a new examination or to make up a specified study, as a condition of remaining in one's class or in college; as, to condition a student who has failed in some branch of study.
v. i.
To impose upon an object those relations or conditions without which knowledge and thought are alleged to be impossible.
a.
Not conditioned or subject to conditions; unconditional.
a.
Expressing a condition or supposition; as, a conditional word, mode, or tense.