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Questions tagged [marginal-probability]

Marginal probability arises from a joint probability measure on a product space. The marginal probability distributions are the push-forward measures induced by the coordinate projections. A marginal probability is the probability of a single cylinder-set event. This is contrast to joint probability or conditional probability, in which additional events are considered.

Marginal probability is the probability of any one single event. This is contrast to joint probability or conditional probability, in which additional events are considered.

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I seem to have wrong math for marginal independence proof (details in question), can anyone explain where my logic went wrong.

I'm not sure but for proofing marginal independence I've came across this stack exchange post, and from there to this link, where I found that the condition to hold for 2 variables to be independent marginally is $P(X \lor Y) = P(X)$ which I assume…
Nikolai Savulkin
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What is the probability that a sample belongs to a particular random variable?

Edited for clarity. Let $X$ be a continuous random variable with a known probability distribution. Let $\mathbf{v}$ be a vector in $\mathbb{R}^n$. What is the probability that $\mathbf{v}$ is a sample of $X$?
Asger Jon Vistisen
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Notation of marginal probabilities

I found a (to me) strange notation concerning marginal probabilities I don’t understand. Unfortunately I will include picture of the notation. Does it mean x=2.5, shouldn’t it be 0 then? Do they mean the cumulative distribution fuchtion? Thanks
Lillys
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