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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
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 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
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
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
Probability puzzle
decision tree. The conditional probability of winning by switching is 1/3/1/3 + 1/6, which is 2/3. The conditional probability table below shows how
Monty_Hall_problem
Topics referred to by the same term
Penning Trap Mass Spectrometer, at Argonne National Laboratory Conditional probability table Cone penetration test, to determine properties of soils Coprecipitation
CPT
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)
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
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
Conceptual model in philosophy of science
disease) the conditional probability table takes the form: According to this table, when a patient does not have the disease, the probability of a positive
Causal_model
Chances of card combinations in poker
Poker probabilities including conditional calculations Numerous poker probability tables 5, 6, and 7 card poker probabilities Hold'em poker probabilities
Poker_probability
Statistical significance test
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 ( a + c a
Fisher's_exact_test
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
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
Table that displays the frequency of variables
the distribution of probability, which can be expressed easily from the contingency table by the relative frequencies. A pivot table is a way to create
Contingency_table
Term in statistical hypothesis testing
, where β {\displaystyle \beta } is the probability of making a type II error (a false negative) conditional on there being a true effect or association
Power_(statistics)
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
Graphical model
networks, DNs may contain cycles. Each node is associated to a conditional probability table, which determines the realization of the random variable given
Dependency network (graphical model)
Dependency_network_(graphical_model)
Intelligence of machines
dealing with uncertain or incomplete information, employing concepts from probability and economics. Many of these algorithms are insufficient for solving
Artificial_intelligence
Probabilistic graphical representation of causal relationships
joint probability function Pr ( G , S , R ) {\displaystyle \Pr(G,S,R)} and the conditional probabilities from the conditional probability tables (CPTs)
Bayesian_network
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
Class of nonparametric methods
X}={\mathcal {C}}_{YX}{\mathcal {C}}_{XX}^{-1},} is in this setting a conditional probability table C Y ∣ X = ( P ( Y = s ∣ X = t ) ) s , t ∈ { 1 , … , K } {\displaystyle
Kernel embedding of distributions
Kernel_embedding_of_distributions
Randomly determined process
(stókhos) 'target, aim, guess') is the property of being well-described by a random probability distribution. Stochasticity and randomness are technically distinct concepts
Stochastic
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
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
Conditional operator in computer programming
In computer programming, the ternary conditional operator is a conditional expression with three parts: the Boolean condition, the then-expression, and
Ternary_conditional_operator
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
Distribution of an uncertain quantity
prior with new information to obtain the posterior probability distribution, which is the conditional distribution of the uncertain quantity given new data
Prior_probability
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
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
Estimate of an unobservable underlying probability density function
conditional on diabetes. The conditional density estimates are then used to construct the probability of diabetes conditional on "glu". The "glu" data were
Density_estimation
Logical connective
The material conditional (also known as material implication) is a binary operation commonly used in logic. When the conditional symbol → {\displaystyle
Material_conditional
Middle quantile of a data set or probability distribution
higher half from the lower half of a data sample, a population, or a probability distribution. For a data set, it may be thought of as the "middle" value
Median
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
1763 mathematics essay by Thomas Bayes
Calculating the Exact Probability of All Conclusions Founded on Induction. The essay includes theorems of conditional probability which form the basis
An Essay Towards Solving a Problem in the Doctrine of Chances
An_Essay_Towards_Solving_a_Problem_in_the_Doctrine_of_Chances
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
Rule of logical inference
base rate (a.k.a. prior probability) of P {\displaystyle P} . The conditional probability Pr ( Q ∣ P ) {\displaystyle \Pr(Q\mid P)} generalizes the logical
Modus_tollens
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
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
Averages of repeated trials converge to the expected value
In probability theory, the law of large numbers is a mathematical law which states that the average of the results obtained from a large number of independent
Law_of_large_numbers
Time series model
In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance
Autoregressive conditional heteroskedasticity
Autoregressive_conditional_heteroskedasticity
Apparent lack of pattern or predictability in events
Randomness applies to concepts of chance, probability, and information entropy. The fields of mathematics, probability, and statistics use formal definitions
Randomness
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
Interpretation of probability
Frequentist probability or frequentism is an interpretation of probability; it defines an event's probability (the long-run probability) as the limit
Frequentist_probability
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
takes value 1 with probability p and value 0 with probability q = 1 − p. The Rademacher distribution, which takes value 1 with probability 1/2 and value −1
List of probability distributions
List_of_probability_distributions
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
Average value of a random variable
In probability theory, the expected value (also called expectation, mean, or first moment) is a generalization of the weighted average. The expected value
Expected_value
Class of statistical models
large class of probability distributions that includes the normal, binomial, Poisson and gamma distributions, among others. The conditional mean μ of the
Generalized_linear_model
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
Process of using data analysis for predicting population data from sample data
probabilities (i.e. probabilities conditional on the observed data), compared to the marginal (but conditioned on unknown parameters) probabilities used
Statistical_inference
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
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
Measure of statistical dispersion
ISBN 0-19-914391-9. Zwillinger, D., Kokoska, S. (2000) CRC Standard Probability and Statistics Tables and Formulae, CRC Press. ISBN 1-58488-059-7 page 18. Ross
Interquartile_range
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
Inference algorithm for probabilistic graphical models
specifically, in Algorithm 2, ϕ {\displaystyle \phi } is the set C of conditional probability tables (henceforth "CPTs") for B, X {\displaystyle X} is a list of
Variable_elimination
Function in actuarial science
the instantaneous conditional rate of death at age x {\displaystyle x} . Formally, it is the limit of the conditional probability of dying in a short
Force_of_mortality
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
Diagnostic plot of binary classifier ability
area under the probability distribution from − ∞ {\displaystyle -\infty } to the discrimination threshold) of the detection probability in the y-axis versus
Receiver operating characteristic
Receiver_operating_characteristic
Terms to describe a conditional relationship between two statements
terms used to describe a conditional or implicational relationship between two statements. For example, in the conditional statement: "If P then Q",
Necessity_and_sufficiency
Measure of covariance of components of a random vector
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance
Covariance_matrix
Concept in inferential statistics
For example, when α {\displaystyle \alpha } is set to 5%, the conditional probability of a type I error, given that the null hypothesis is true, is 5%
Statistical_significance
Survival model in actuarial science
is the future lifetime of (x) (T(x) is a random variable). The conditional probability that (x) survives to age x+t is Pr[T(0) ≥ x+t | T(0) ≥ x] = S(x+t)
De_Moivre's_law
Variable representing a random phenomenon
uncertainty, such as measurement error. However, the interpretation of probability is philosophically complicated, and even in specific cases is not always
Random_variable
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
expectation Conditional independence Conditional probability Conditional probability distribution Conditional random field Conditional variance Conditionality principle
List_of_statistics_articles
Risk measure estimating the average loss in the worst tail of the distribution
shortfall is also called conditional value at risk (CVaR), average value at risk (AVaR), tail value at risk (TVaR), conditional tail expectation (CTE),
Expected_shortfall
Approximation method in statistics
of probability and to the normal distribution. He had managed to complete Laplace's program of specifying a mathematical form of the probability density
Least_squares
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
Number of occurrences in an experiment or study
distribution, while the body of the table reports the joint frequencies. Under the frequency interpretation of probability, it is assumed that the source is
Frequency_(statistics)
Selection of data points in statistics
the sample design, particularly in stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In
Sampling_(statistics)
Concepts from statistical hypothesis testing
statistical hypothesis tests have a probability of making type I and type II errors. The type I error rate is the probability of rejecting the null hypothesis
Type_I_and_type_II_errors
Covariance and correlation
a peak at a lag of zero, and its size will be the signal energy. In probability and statistics, the term cross-correlations refers to the correlations
Cross-correlation
Applications of logic under uncertainty
Probabilistic logic (also probability logic and probabilistic reasoning) involves the use of probability and logic to deal with uncertain situations. Probabilistic
Probabilistic_logic
Probabilistic classification algorithm
model on probability tables is infeasible. The model must therefore be reformulated to make it more tractable. Using Bayes' theorem, the conditional probability
Naive_Bayes_classifier
Measure of the joint variability
In probability theory and statistics, covariance is a measure of the joint variability of two random variables. The sign of the covariance shows the tendency
Covariance
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
Branch of statistics
Mathematical statistics is the application of probability theory and other mathematical concepts to statistics, as opposed to techniques for collecting
Mathematical_statistics
Sequence of data points over time
over time (heteroskedasticity). These models represent autoregressive conditional heteroskedasticity (ARCH) and the collection comprises a wide variety
Time_series
Type of statistics
Cross-tabulations and contingency tables Graphical representation via scatterplots Quantitative measures of dependence Descriptions of conditional distributions The main
Descriptive_statistics
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
paradox / iex (2:CM) Conditional expectation / (2:BDR) Conditional independence / (3F:BR) Conditional probability Conditional probability distribution / (2:DC)
Catalog of articles in probability theory
Catalog_of_articles_in_probability_theory
Probabilistic model
graph expresses the conditional dependence structure between random variables. Graphical models are commonly used in probability theory, statistics—particularly
Graphical_model
Problem in statistical estimation
written ( n ∣ m , k ) {\displaystyle (n\mid m,k)} . The rule for conditional probability gives ( n ∣ m , k ) ( m ∣ k ) = ( m ∣ n , k ) ( n ∣ k ) = ( m
German_tank_problem
Non-parametric method for testing whether samples originate from the same distribution
probability distribution of H {\displaystyle H} can be quite different from this chi-squared distribution. If a table of the chi-squared probability distribution
Kruskal–Wallis_test
Statistical hypothesis test
statistic requires one to assume that the discrete probability of observed binomial frequencies in the table can be approximated by the continuous chi-squared
Chi-squared_test
Relative measure of dispersion expressed as the ratio of standard deviation to the mean
In probability theory and statistics, the coefficient of variation (CV), also known as normalized root-mean-square deviation (NRMSD), and relative standard
Coefficient_of_variation
Measure of variation in statistics
deviation of a random variable, sample, statistical population, data set or probability distribution is the square root of its variance (the variance being the
Standard_deviation
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
Mathematical statistics distance measure
is roughly a symmetrization of conditional entropy. It is a metric on the set of partitions of a discrete probability space. MAUVE is a measure of the
Kullback–Leibler_divergence
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
Statistical hypothesis test for forecasting
this, a conditional intensity function is used to represent the probability of a neuron spiking, conditioned on its own history. The conditional intensity
Granger_causality
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)
Type of average of a collection of numbers
integers, then the probability of a number falling into some range of possible values can be described by integrating a continuous probability distribution
Arithmetic_mean
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
Statistical test comparing two probability distributions
2.2), one-dimensional probability distributions. It can be used to test whether a sample came from a given reference probability distribution (one-sample
Kolmogorov–Smirnov_test
Branch of statistics
formulated as follows. By definition the likelihood function is the conditional probability of the data given the parameters of the model. It is customary
Survival_analysis
Statistical property
heteroscedasticity, which led to his formulation of the autoregressive conditional heteroscedasticity (ARCH) modeling technique. Consider the linear regression
Homoscedasticity and heteroscedasticity
Homoscedasticity_and_heteroscedasticity
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
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
Girl/Female
Indian
Circumstance, Period of life, Wick, Condition, Degree
Girl/Female
Tamil
Good or Happy condition, Solution, Fortune
Girl/Female
Tamil
Circumstance, Period of life, Wick, Condition, Degree
Boy/Male
Indian
Can Travel in All Climatic Conditions
Girl/Female
Hindu
Good or Happy condition, Solution
Surname or Lastname
Welsh
Welsh : Anglicized form of Welsh ap Rhiddid ‘son of Rhiddid’, a personal name of unexplained etymology.Welsh : Anglicized form of ap Redith ‘son of Redith’, a short form of Meredith; the short form occurs only in this Anglicized spelling.Welsh : from the personal name Predyr, Peredur (perhaps from Old Welsh peri ‘spears’ + dur ‘hard’, ‘steel’), which was borne, in Arthurian legend, by one of the knights of the Round Table.Welsh : occupational name, from Welsh prydydd ‘bard’.English : habitational name from Priddy in Somerset, named probably with Celtic words meaning ‘earth house’.
Boy/Male
Bengali, Indian
Sleepless; Condition of Being Awake; One who Conquers Sleep
Surname or Lastname
English (of Norman origin)
English (of Norman origin) : occupational name denoting a servant who carried the ewer to guests at table so that they could wash their hands, Anglo-Norman French and Middle English ewerer (related to ewere ‘jug’), with the French definite article l’.Cornish : variant of Flower 4.
Boy/Male
African, Arabic, Australian, French, Indian, Muslim, Sindhi
Sacrifice; Unconditional Love; Love
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.
Boy/Male
Arabic
State; Condition
Surname or Lastname
English
English : from Middle English chike ‘young fowl’ (a shortened form of chiken), applied as a metonymic occupational name for someone who bred poultry for the table, or as a nickname from the same word used as a term of endearment.English : variant of Cheek.
Surname or Lastname
English (of Norman origin)
English (of Norman origin) : occupational name from Old French tablier ‘joiner’.
Surname or Lastname
Welsh
Welsh : Anglicized form of the Welsh patronymic ap Heilyn ‘son of Heilyn’, which is probably a derivative of a word meaning ‘to serve at table’.English : habitational name from Palling in Norfolk or Poling in Sussex. These were named in Old English with the personal names Pælli and PÄl respectively, + -ingas ‘followers of’, ‘dependants of’.French : unexplained.A Palin, also written Palen and Pallin, from the Poitou region of France, is documented in Quebec City in 1692, with the secondary surname Dabonville.
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 : metonymic occupational name for a producer or seller of table linen, from Old French nappe ‘table cloth’.English : either a variant spelling of Knapp or a reduced variant of Scottish McNabb.Altered spelling of German Knapp.German : metonymic occupational name for a bowl and cup maker, from Middle Low German nap ‘bowl’, ‘mug’, or alternatively, from an old personal name formed with an element cognate with Old High German (gi-)nÄda ‘grace’, ‘benevolence’.
Girl/Female
Hindu
Good or Happy condition, Solution, Fortune
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
Boy/Male
Tamil
Bright, Very bright, Happiness
Boy/Male
Biblical Hebrew
He that weeps or cries.
Boy/Male
Muslim
Ambassador, Handsome, Emissary, Mediator
Boy/Male
Tamil
Marutatmaj | மாஂரà¯à®¤à®¾à®¤à¯à®®à®œÂ
Most beloved like gems
Boy/Male
Indian, Telugu
Lord Rama and Krishna
Girl/Female
Tamil
Well wisher
Surname or Lastname
English
English : habitational name from Whelpley Hill in Ashley Green, Buckinghamshire or from places called Whelpley in Hailsham, Sussex, and Whiteparish, Wiltshire, all named with Old English hwelp ‘whelp’, ‘cub’, ‘young animal’ + lēah ‘(woodland) clearing’.
Female
Gypsy/Romani
 Possibly a Romani form of French Fifi, FIFIKA means "(God) shall add (another son)."Â
Surname or Lastname
English (Lancashire)
English (Lancashire) : habitational name from a place near Manchester, so named from Old English hind ‘female deer’ + lēah ‘wood’, ‘clearing’.
Boy/Male
Hindu
Name from vishnusahstranaam
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
CONDITIONAL PROBABILITY-TABLE
n.
Probability.
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.
Expressing a condition or supposition; as, a conditional word, mode, or tense.
n.
Probability.
n.
Likelihood; probability.
a.
Not conditional limited, or conditioned; made without condition; absolute; unreserved; as, an unconditional surrender.
a.
Unconditional.
imp. & p. p.
of Condition
adv.
Conditionally.
n.
A conditional word, mode, or proposition.
a.
Surrounded; circumstanced; in a certain state or condition, as of property or health; as, a well conditioned man.
n.
One who maintains that certainty is impossible, and that probability alone is to govern our faith and actions.
v. t.
Conditional.
n.
The doctrine of the probabilists.
adv.
In a conditional manner; subject to a condition or conditions; not absolutely or positively.
superl.
Having probability; affording probability; probable; likely.
v. t.
To put under conditions; to render conditional.
a.
Containing, implying, or depending on, a condition or conditions; not absolute; made or granted on certain terms; as, a conditional promise.
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.
a.
Not conditioned or subject to conditions; unconditional.