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Suppose I have two random variables:

Control = BetaDistribution[24,141]
Var = BetaDistribution[30,151]

I can sample from this easy enough with RandomVariate[Var, 10] and calculate the probability that one of the distributions is greater than a constant, e.g. Probability[x <= .2, x \[Distributed] Var].

But how do I calculate $P(Var>Control)$. Many thanks!

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Very similar:

Probability[
 control < var, {control \[Distributed] BetaDistribution[24, 141], 
  var \[Distributed] BetaDistribution[30, 151]}]

1191614106688032995829016253297371 / 1700223091652404809206230640390474

(roughly 0.7)

Verify numerically:

control = BetaDistribution[24, 141]
var = BetaDistribution[30, 151]
Count[Thread[
  RandomVariate[control, 1000000] < 
   RandomVariate[var, 1000000]], True]

also roughly 0.7

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    $\begingroup$ Thanks! That's what I was looking for. One more question. How would I do it with a declared variable -- I'm not sure on the syntax there, e.g. something like: Control = BetaDistribution[24,141]; Var = BetaDistribution[30,151]; Probability[Control < Var, {Control, Var}] $\endgroup$
    – toomey8
    Sep 18 '21 at 15:29
  • $\begingroup$ control = BetaDistribution[24, 141]; var = BetaDistribution[30, 151]; Probability[c < v, {c \[Distributed] control, v \[Distributed] var}] $\endgroup$
    – SHuisman
    Sep 18 '21 at 15:36
  • 1
    $\begingroup$ Thanks, that's perfect! $\endgroup$
    – toomey8
    Sep 18 '21 at 15:42

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