Expected Value and Arrival Times

Joe, Austin, and Garren are studying for their final Probability exam and agree to meet at 8.00pm. They will not arrive before the specified meeting time. Their lateness (the amount of time by which they are late) are independent and exponentially distributed with an average lateness of 120 seconds. Suppose T 1 , T 2 , T 3 T_1, T_2, T_3 are the lateness in seconds of the first, second, and third people to arrive, respectively. Find E [ T 1 T 3 = 120 ] \mathbb{E}[T_1 | T_3 = 120] .

Assumptions : T 1 , T 2 , T 3 T_1, T_2, T_3 are defined according to the order they arrive. They are not defined as Joe's, Austin's, and Garren's in that order. For example, if it's Garren that arrives first, then T 1 T_1 is Garren's lateness. The answer is expressed in seconds.

97.34 14.7 30.8 60

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1 solution

Nicola Mignoni
Aug 6, 2019

Given that

T i 1 120 e t i 120 , i { 1 , 2 , 3 } \displaystyle T_i \sim \frac{1}{120}e^{-\frac{t_i}{120}}, \ i \in \{1,2,3\}

and

P ( T i T j ) = P ( T i ) , i , j { 1 , 2 , 3 } , i j \displaystyle \mathbb{P}(T_i | T_j)=\mathbb{P}(T_i), \ \ i,j \in\{1,2,3\}, \ \ i \neq j

we have that

E ( T 1 T 3 = 120 ) = 0 + t 1 f T 1 T 3 ( t 1 t 3 ) d t 1 = 0 120 t 1 120 e t 1 120 d t 1 \displaystyle \mathbb{E}(T_1 | T_3=120)=\int_{0}^{+ \infty} t_1 f_{T_1|T_3} (t_1|t_3) dt_1=\int_{0}^{120} \frac{ t_1}{120}e^{-\frac{t_1}{120}} dt_1

since f T 1 T 3 ( t 1 t 3 ) = f T 1 ( t 1 ) \displaystyle f_{T_1|T_3} (t_1|t_3)=f_{T_1}(t_1) . Let t 1 = t t_1=t . Solving the integral via integration by parts we have

E ( T 1 T 3 = 120 ) = 0 120 t 120 e t 120 d t = [ t e t 120 ] 0 120 + 0 120 e t 120 d t = 120 e + [ 120 e t 120 ] 0 120 = 120 240 e = 31.708 \displaystyle \mathbb{E}(T_1 | T_3=120) = \int_{0}^{120} \frac{ t}{120}e^{-\frac{t}{120}} dt=\big[-t\cdot e^{-\frac{t}{120}}\big]_{0}^{120}+\int_{0}^{120} e^{-\frac{t}{120}} dt=-\frac{120}{e}+\big[-120e^{-\frac{t}{120}}\big]_{0}^{120}=120-\frac{240}{e}=\boxed{31.708}

Your method and the final answer are both incorrect. The order statsitics of exponential distribution are not independent to each other.

Pi Maths - 3 months, 3 weeks ago

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