Sebaran probabilitas: Béda antarrépisi
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Dina [[matematika]], '''sebaran probabilitas''' nangtukeun unggal [[interval (matematika)|interval]] tina [[wilangan nyata]] [[kamungkinan]], mangka kitu [[aksioma probabilitas]] ''terpenuhi''. Dina watesan teknik, probabiliti sebaran
Probabilitas sebaran dina kasus husus
Unggal [[variabel acak]] gives rise to a probability distribution, and this distribution contains most of the important information about the variable. If ''X'' is a random variable, the corresponding probability distribution assigns to the interval [''a'', ''b''] the probability Pr[''a'' ≤ ''X'' ≤ ''b''], i.e. the probability that the variable ''X'' will take a value in the interval [''a'', ''b''].
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pikeun ''x'' anggota '''R'''.
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A distribution is called ''discrete'' if its cumulative distribution function consists of a sequence of finite jumps, which
A distribution is called ''continuous'' if its cumulative distribution function is [[continuous]], which
The so-called ''absolutely continuous distributions'' can be expressed by a [[fungsi dénsitas probabilitas]]: a non-negative [[Lebesgue integration|Lebesgue integrable]] function ''f'' defined on the
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== Jejer penting dina sebaran probabiliti ==
Sababaraha sebaran probabiliti kacida pentingna dina
* Sebaran diskrit
** Dina kaayaan terhingga
*** [[degenerate distribution|Sebaran ''degenerate'']] dina ''x''<sub>0</sub>, numana ''X''
*** The discrete [[sebaran seragam|uniform distribution]], where all elements of a finite [[set theory|set]] are equally likely. This is supposed to be the distribution of a balanced coin, an unbiased die, a casino roulette or a well-shuffled deck. Also, one can use
*** The [[Bernoulli distribution]], which takes value 1 with probability ''p'' and value 0 with probability ''q''=1-''p''.
*** [[Sebaran binomial]], nu ngajelaskeun jumlah kasuksesan dina deret tina percobaan bebas Enya/Henteu.
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** With infinite support
*** The [[geometric distribution]], a discrete distribution which describes the number of attempts needed to get the first success in a series of independent Yes/No experiments.
*** The [[negative binomial distribution]], a generalization of the
*** The [[Poisson distribution]], which describes the number of rare events that happen in a certain time interval.
*** The [[Boltzmann distribution]], a discrete distribution important in [[statistical physics]] which describes the probabilities of the various discrete energy levels of a system in [[thermal equilibrium]]. It has a contiuous analogue. Special cases include
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**** The [[Bose-Einstein distribution]]
**** The [[Fermi-Dirac distribution]]
*** The [[zeta distribution]] has uses in applied statistics and statistical mechanics, and perhaps may be of interest to number
* Continuous distributions
** Supported on a finite interval
*** [[sebaran seragam]] dina [''a'',''b''], numana
*** [[Sebaran beta]] dina [0,1],
*** The [[Triangular distribution]] on [a, b]
** Supported on semi-infinite intervals, usually [0,∞)
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*** The [[Log-normal distribution]], describing variables which can be modelled as the product of many small independent positive variables.
*** The [[Weibull distribution]], of which the exponential distribution is a special case, is used to model the lifetime of technical devices.
*** [[Sebaran chi-kuadrat]], nu
*** [[Sebaran-F]], numana sebaran rasio dua sebaran variabel normal,
** Supported on the whole
*** [[Sebaran normal]], disebut
*** [[Sebaran-t student]],
*** [[Sebaran Cauchy]], conto sebaran nu teu ngabogaan [[nilai ekspektasi]] atawa [[varian]]. Dina fisika biasana disebut Lorentzian, sarta ieu sebaran tina tetapan
* Joint distributions
** Two or more random variables on the same sample space
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