Two people agree to meet at a specified place between 3:00
P.M. and 4:00 P.M. Suppose that you measure time to the nearest
minute relative to 3:00 P.M. so that, for instance, time 40
represents 3:40 P.M. Further suppose that each person arrives
according to the discrete uniform distribution on {0, 1, ..., 60}
and that the two arrival times are independent. Determine the
expected time until the first arrival.
Here I've tried setting :
Xi=person i's arrival time with i=1,2
PX(xi)={1/61,if xi ∈[0,1,2,3...60]0,otherwise
I create a function Z=min{x,y}
E(z)=60∑z=0zPZ(z)=60∑z=0z[P(x1=z,x2>z)+P(x1>z,x2=z)+P(x1=z,x2=z)]
And that is where I'm kind of stuck because
I've tried rewrittin P(x1=z,x2>z) as P(x2>z)P(x1=z|x2>z) and drawing a little pmf table but still no luck.
If anybody by any chance knows a much easier way to solve this problem I would be happy to hear from them.
Answer
A reusable trick . . .
Since the values of z are nonnegative integers, it follows that
E(z)=p1+p2+p3+⋯
where pk=P(z≥k).
Hence we get
E(z)=60∑k=1(61−k61)2=121061≈19.84
To explain the trick . . .
For each positive integer k, let qk=P(z=k).
Then we have
p1=q1+q2+q3+⋯p2=q1+q2+q3+⋯p3=q1+q2+q3+⋯⋮
hence, summing the columns, we get
p1+p2+p3+⋯=1q1+2q2+3q3+⋯
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