Examples of using Probability distribution in English and their translations into Hungarian
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Continuous probability distribution.
Where the idea of“random variable” entersis when a function is combined with a probability distribution.
The probability distribution of X appears in the following table.
Cumulative distribution function, or cumulative probability distribution function.
This probability distribution is named after James Clerk Maxwell and Ludwig Boltzmann.
Where the expected values are with respect to some probability distribution in the random variable X.
C Probability distribution, telling us how likely different outcomes are.
The conceptual background of this problem os provided by snapshot attractors and their natural probability distribution.
A probability distribution is considered uniform if every outcome is equally as likely.
This approach involves the use of range values of output parameters(probability distribution is performed).
A Probability Distribution represents how frequently different values occur.
Is it reasonable to include the novel in the set of“possible novels”,or even to postulate some probability distribution for this set?
If the probability distribution is symmetrical, the expected value will be the middle one.
If there are g(E)dE states with energy E to E+dE,then the Boltzmann distribution predicts a probability distribution for the energy.
The PageRanks form a probability distribution over the web pages, so the sum of all web pages' PageRanks is one.
In information theory,it is common to start with memoryless channels in which the output probability distribution only depends on the current channel input.
Probability distribution forecast means a mathematical function that assigns to an exhaustive set of mutually exclusive future events a probability of realisation;
Consequently the future can be reliably forecasted by analyzingpast and current market data to obtain the probability distribution governing future events.
A probability distribution is a sample space where every item has a probability value between 0 and 1 assigned to them that represents how likely they are to be picked.
Consequently the future can be reliably forecasted by analyzing past andcurrent market data to obtain the probability distribution governing future events.
All of this carries directly over to the general continuous case: the weights ai arereplaced by a non-negative integrable function f(x), such as a probability distribution, and the summations are replaced by integrals.
It is assumedhere that a random sample is obtained from a probability distribution, and that we want to know if the tail of the distribution follows a power law(in other words, we want to know if the distribution has a"Pareto tail").
Harsanyi postulated that every player is one of several"types", where each type corresponds to a set of possible preferences for the player anda(subjective) probability distribution over the other players' types.
The principal goal of this researchtopic is to develop a method to determine the probability distribution of the dynamic water surface elevations and wind waves along the shoreline of shallow, medium-sized lakes, and demonstrate its applicability in a real case study.
In other words, somehow today's rational market participantspossess statistically reliable information regarding the probability distribution of the universe of future events that will can occur on any specific future date.
Because a probability distribution Pr on the real line is determined by the probability of a real-valued random variable X being in a half-open interval-∞,x, the probability distribution is completely characterized by its cumulative distribution function.
To associate a specific level of confidence with the interval defined by the expanded uncertainty requires explicit orimplicit assumptions regarding the probability distribution characterized by the measurement result and its combined standard uncertainty.
In this way, an IID sequence is different from a Markov sequence,where the probability distribution for the nth random variable is a function of the previous random variable in the sequence(for a first order Markov sequence). An IID sequence does not imply the probabilities for all elements of the sample space or event space must be the same.[3] For example, repeated throws of loaded dice will produce a sequence that is IID, despite the outcomes being biased.
A(η) is called the log-partition function because it is the logarithm of a normalization factor, without which f X( x; θ){\displaystyle f_{X}(x;\theta)}would not be a probability distribution("partition function" is often used in statistics as a synonym of"normalization factor").
