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probability distribution
This term is a technical expression used primarily in statistics, mathematics, and data science. It describes the theoretical behavior of a random variable, mapping every possible outcome to its likelihood of occurrence. While a single probability refers to one event, the distribution encompasses the entire set of possibilities.
In professional and academic registers, it is often categorized into discrete distributions, where outcomes are countable, and continuous distributions, where outcomes can take any value within a range. Misusing this term in a casual context may sound overly clinical or precise, as it implies a rigorous mathematical framework rather than a general guess about the future.
Ý nghĩa
A mathematical function that provides the probabilities of occurrence of different possible outcomes for an experiment or a random variable.
Ví dụ
The professor explained how to calculate the probability distribution for a discrete random variable.
The professor explained how to calculate the probability distribution for a discrete random variable.
We need to determine the probability distribution of the errors to improve our model.
Does this data follow a normal probability distribution or is it skewed?
Does this data follow a normal probability distribution or is it skewed?
I wonder if the probability distribution of the dice rolls is actually uniform.
The analyst plotted the probability distribution to visualize the likelihood of different outcomes.
The analyst plotted the probability distribution to visualize the likelihood of different outcomes.
A binomial probability distribution is used when there are only two possible outcomes.
A binomial probability distribution is used when there are only two possible outcomes.
The probability distribution of the test scores showed a clear bell curve.
The probability distribution of the test scores showed a clear bell curve.
He spent hours trying to derive the exact probability distribution for the complex system.
Let us assume a uniform probability distribution for the initial parameters.
Let us assume a uniform probability distribution for the initial parameters.