Examples of using Probability distribution in English and their translations into Arabic
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(d) Probability distributions.
Perplexity of a probability distribution.
Its probability distribution assigns a probability(x) to each possible value.
Random variables and probability distributions.
In the"Land of the usual" focusphenomenon, which can be described using traditional statistical concepts, such as normal probability distribution.
(c) Normal probability distributions.
Is between and inclusive, which meets the first property of the probability distribution.
(b) Continuous probability distributions.
Cells were well differentiated, slow growing, low probability distribution.
All you can know is a probability distribution of where it is likely to be.
When you first told me you wanted to run an advanced conditional probability distribution application.
He obtained the probability distributions of statistics relating to several multivariate procedures.
In natural language processing, perplexity is a way of evaluating language models.A language model is a probability distribution over entire sentences or texts.
It is assumed that there is a"true" probability distribution induced by the process that generates the observed data.
The simulation programme, called MARK3, combines the estimates of the number of undiscovered deposits with the historical grades and tonnages of the deposits represented by the grade-tonnagemodels developed for each type of deposit to produce a probability distribution of the quantities of contained mineral commodities.
The perplexity of a discrete probability distribution p is defined as.
The probability distribution of the projected evolution of the debt ratio is then used like an early warning system, which triggers policy advice to countries that are on an unsustainable path.
The activity times are assumed to be random,with assumed probability distribution("probabilistic"). They are represented by arrowed lines between nodes or circles.
The posterior probability distribution of one random variable given the value of another can be calculated with Bayes' theorem by multiplying the prior probability distribution by the likelihood function, and then dividing by the normalizing constant, as follows.
For example, if readings are taken of temperature and wind speed,each would be described by its own probability distribution, as knowing the reading for one measurement would not provide any information about the other.
These probability distributions illustrate that every possible configuration of the field is possible, with the amplitude of quantum fluctuations controlled by Planck's constant ℏ{\displaystyle\hbar}, just as the amplitude of thermal fluctuations is controlled by k B T{\displaystyle k_{\mathrm{B}}T}, where kB is Boltzmann's constant. Note that the following three points are closely related.
(a) A walker in a circular corral. Trajectories of increasing lengthare colour-coded according to the droplet's local speed(b) The probability distribution of the walker's position corresponds roughly to the amplitude of the corral's Faraday wave mode.[17].
The IMF is often given as a probability distribution function(PDF) for the mass at which a star enters the main sequence(begins hydrogen fusion).
In general the b-ary entropy of a source S{\displaystyle{\mathcal{S}}}= (S, P) with source alphabet S= {a1,…, an} and discrete probability distribution P= {p1, …, pn} where pi is the probability of ai(say pi = p(ai)) is defined by.
Let us have a prior belief that the probability distribution function is p( θ){\displaystyle p(\theta)} and observations x{\displaystyle x} with the likelihood p( x | θ){\displaystyle p(x|\theta)}, then the posterior probability is defined as.
This course aims to teach students statistical analysis methods of data and its applications in quality. In addition,this course aims to study descriptive statistics, probability distributions, correlation and regression, hypotheses testing, analysis of variance, confidence limits and illustrate how to use these statistical methods in quality by using SPSS, excel, Minitab.
In formal terms, there is no free lunch when the probability distribution on problem instances is such that all problem solvers have identically distributed results. In the case of search, a problem instance is an objective function, and a result is a sequence of values obtained in evaluation of candidate solutions in the domain of the function. For typical interpretations of results, search is an optimization process.
The statistical relationship between the error terms and the regressors plays an important role in determining whether an estimation procedure has desirable sampling properties such as being unbiased and consistent.The arrangement, or probability distribution of the predictor variables x has a major influence on the precision of estimates of β. Sampling and design of experiments are highly developed subfields of statistics that provide guidance for collecting data in such a way to achieve a precise estimate of β.
In information theory, perplexity is a measurement of how well a probability distribution or probability model predicts a sample. It may be used to compare probability models.A low perplexity indicates the probability distribution is good at predicting the sample.
Leslie's argument differs from Gott's version in that hedoes not assume a vague prior probability distribution for N. Instead he argues that the force of the Doomsday Argument resides purely in the increased probability of an early Doomsday once you take into account your birth position, regardless of your prior probability distribution for N. He calls this the probability shift.