# Questions tagged [conditioning]

Conditioning is a probabilistic operation that consists in examining the probabilistic properties of a random variable (or of an event) given the realised value of another random variable (or of an event)

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### How do i solve this problem on conditional probability [closed]

Where x~ u(0,4), what is P(X>Y|X<2Y) I know that X lies between Y at the lower bound and 2Y at the upper bound but i am having trouble trying to figure out P(X<2Y) as none of the examples i ...
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### How to choose what to integrate out or what to condition on for marginal distributions?

I am trying to work out the Bayesian posteriors of $\theta$, $\tau$ and the $\varepsilon$ in the following model: $$y(t) = \phi(t,\tau)\theta+v(t),$$ where $\{v(t)\}$ is an iid sequence of random ...
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### When and how of stratification?

I understand stratification at a novice level. For example, if we want to condition on gender in post experimentation inference, we might stratify or block on gender. As I understand it, we take each ...
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### conditional probabilities in chess

Let's say I am analyzing certain chess positions of a chess player (Magnus Carlsen, Lichess games when playing as white). We know that the 'unconditional probability' (empirically speaking) of this ...
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### Is there a difference in interpretation between $Y|X = m(X) + \epsilon$ vs. $Y = m(X) + \epsilon$?

I understand that $E(Y|X)$ and $E(Y)$ are different, but difference sources, when $Y$ is a function of other random variables such as $X$, use $Y|X$ and $Y$ to describe this relationship. I'm not sure ...
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### Why condition on either the r.v. $X$ or $Y$ and integrate over a product of pdfs rather a single pdf to find this probability density?

Let $X$ have the probability density $f_{X}(x)=\lambda e^{-\lambda x}, \;\; x>0$ and let $Y$ have the probability density $f_{Y}(y)=\lambda e^{-\lambda x},\;\; y>0.$ Find the probability ...
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### What does the assumption of the Fisher test that "The row and column totals should be fixed" mean?

As this source states, one of the assumptions to perform Fisher's exact test of independence is that the row and column totals should be fixed. However, I find the explanation coming with it pretty ...
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### conditioning for deep neural networks

What is the best way to do conditioning when working with deep neural nets? For example, say we we want to condition a VAE on the class i.e. CVAE. There exists different ways of adding the class to ...
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Suppose X, Z are normally distributed random variables and independent ($X$ follows $N(\mu,\sigma^{2})$ and $Z$ follows $N(0,\sigma_{z}^{2})$), and that Y=X+Z. What is E[X|Y>c], where c is just a ...
Let the joint pdf of $X$ and $Y$ be $f(x,y) = 12e^{-4x-3y}, x>0, y>0$. What is the marginal cdf of $X$? of $Y$? Am I just supposed to integrate f(x,y) with respect to $x$ or $y$ to get the ...