Finding probability of a minimum

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The discussion centers on calculating the probability of the minimum of two discrete random variables, X1 and X2, where Y=min(X1,X2). The correct formula for P(Y=1) is P[(X1=1) and (X2>=1)] + P[(X2=1) and (X1>=2)], as stated in the referenced book. The confusion arises from the asymmetry in the probabilities, which is valid for discrete distributions but not for continuous distributions. The participants clarify that the method proposed by one user is only applicable to continuous random variables, where the event of both variables equaling one has zero probability.

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torquerotates
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let X1 and X2 be two randomly selected random variables from the same discrete distribution. Let Y=min(X1,X2). Find P(Y=1)

according to the book. P(Y=1)=P[(X1=1)and(X2>=1)]+P[(X2=1)and(X1>=2)]

I don't understand why is the asymmetry is even possible. The way I look at it, it's
P(Y=1)=P[(X1=1)and(X2>1)]+P[(X2=1)and(X1>1)]
 
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torquerotates said:
according to the book. P(Y=1)=P[(X1=1)and(X2>=1)]+P[(X2=1)and(X1>=2)]

The way I look at it, it's
P(Y=1)=P[(X1=1)and(X2>1)]+P[(X2=1)and(X1>1)]

In the case of discrete random variables, your way omits the event "X1 = 1 and X2 = 1". In the case of continuous random variables (where that event has zero probability), your method is correct.

The book's way is correct for the case of discrete random variables that only take integer values. It wouldn't be correct for continuous random variables.
 

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