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I have a probabilistic function f(x) which returns True or False depending on its input x. The input x is an integer on the range [1,28] and is chosen uniformly at random.

f(x) behaves as follows:

  • If x == 15 or x == 20, return True with 50% probability otherwise False
  • Else If 15 < x < 20, return True
  • Else return False

How many times does f(x) need to be called before getting a True, on average?

I've simulated this in code already, and what I'm interested in is a solution using probability and statistics.

I've thought about treating f(x) as a coin flip with probability of heads being 4/28 (for the range 15 < x < 20), and then using the expectation of a geometric RV to arrive at 7 flips until the first heads.

However I'm unsure of how to include the 50% probability of True when x == 15 or x == 20. It should reduce the expectation.

I'd appreciate any help.

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    $\begingroup$ Calculate the probability that true is returned on the first call. Use the law of total probability en.wikipedia.org/wiki/Law_of_total_probability to do that, i.e,, condition on something. $\endgroup$
    – Mark L. Stone
    Commented Oct 1, 2016 at 20:19
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    $\begingroup$ Thanks, thinking about it in terms of the first call makes it simpler. That effectively adjusts my p for Geo(p). Using total probability it becomes P(True) = 4/28 + (2/28)*(1/2) = 5/28, which gives E[Geo(5/28)] = 5.6, which is what my program gave me. $\endgroup$
    – caring-goat-913
    Commented Oct 1, 2016 at 20:39

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You are right that $P(15 < X < 20) = 4/28$. As about $15$ or $20$ it's $1/28$ in each case and then you flip a fair coin. Since the probability of coin flips outcome is independent of drawing $15$ or $20$, those events are independent and we multiply independent probabilities. From here you can easily find the answer.

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