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Mar
12
comment Dice game modelling: Lose everything on “3”, double everything on “1” or “6”
$F$ is the value function and $x$ is the earnings or the amount of money you have.
Mar
12
revised Probability Mass Function of largest number selected without replacement
added 1 characters in body
Mar
12
revised Dice game modelling: Lose everything on “3”, double everything on “1” or “6”
added 132 characters in body
Mar
12
answered Dice game modelling: Lose everything on “3”, double everything on “1” or “6”
Mar
12
revised Probability Mass Function of largest number selected without replacement
clarified title with extra words.
Mar
12
suggested approved edit on Probability Mass Function of largest number selected without replacement
Mar
12
revised Probability Mass Function of largest number selected without replacement
edited body
Mar
12
answered Probability Mass Function of largest number selected without replacement
Mar
12
revised Probability Mass Function of largest number selected without replacement
Edited and added latexing for clarity.
Mar
12
suggested approved edit on Probability Mass Function of largest number selected without replacement
Mar
11
awarded  Nice Question
Mar
9
comment Conditional expectation in the case of $\mathcal{A}=\{\emptyset,\Omega,A,A^c\}$
@cardinal: Thanks, edited.
Mar
9
revised Conditional expectation in the case of $\mathcal{A}=\{\emptyset,\Omega,A,A^c\}$
added 8 characters in body
Mar
9
answered Conditional expectation in the case of $\mathcal{A}=\{\emptyset,\Omega,A,A^c\}$
Mar
9
answered Distribution of Product of Random Variables with one being the normal distribution.
Mar
9
comment Let $X$ a random variable with a strictly increasing distrubution function $F_X$. Show that $Y=F_X(X) \sim \hom(0,1)$ distrubution.
$Y=F_X(X)$, so the random variable $Y$ can take values only in $[0,1]$.
Mar
9
revised Let $X$ a random variable with a strictly increasing distrubution function $F_X$. Show that $Y=F_X(X) \sim \hom(0,1)$ distrubution.
added 223 characters in body
Mar
9
answered Let $X$ a random variable with a strictly increasing distrubution function $F_X$. Show that $Y=F_X(X) \sim \hom(0,1)$ distrubution.
Mar
9
answered Mixture Gaussian distribution quantiles
Mar
8
revised Boundedness of expected reward Markov chain (may be related to discret $M/M/\infty$ queue)
basic notation improvement...