Chapter 6: Problem 47
If 3 trucks break down at points randomly distributed on a road of length \(L\), find the probability that no 2 of the trucks are within a distance \(d\) of each other when \(d \leq L / 2\).
/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none}
Learning Materials
Features
Discover
Chapter 6: Problem 47
If 3 trucks break down at points randomly distributed on a road of length \(L\), find the probability that no 2 of the trucks are within a distance \(d\) of each other when \(d \leq L / 2\).
All the tools & learning materials you need for study success - in one app.
Get started for free
The joint density of \(X\) and \(Y\) is given by
$$
f(x, y)= \begin{cases}x e^{-(x+y)} & x>0, y>0 \\ 0 & \text { otherwise
}\end{cases}
$$
Are \(X\) and \(Y\) independent? What if \(f(x, y)\) were given by
$$
f(x, y)= \begin{cases}2 & 0
Suppose that \(10^{6}\) people arrive at a service station at times that are independent random variables, each of which is uniformly distributed over \(\left(0,10^{6}\right)\). Let \(N\) denote the number that arrive in the first hour. Find an approximation for \(P\\{N=i\\}\)
Suggest a procedure for using Buffon's needle problem to estimate \(\pi\). Surprisingly enough, this was once a common method of evaluating \(\pi\).
If \(X\) and \(Y\) are independent continuous positive random variables, express the density function of (a) \(Z=X / Y\) and (b) \(Z=X Y\) in terms of the density functions of \(X\) and \(Y\). Evaluate these expressions in the special case where \(X\) and \(Y\) are both exponential random variables.
Let \(X_{(1)} \leq X_{(2)} \leq \cdots \leq X_{(n)}\) be the ordered values of \(n\) independent uniform \((0,1)\) random variables. Prove that for \(1 \leq k \leq n+1\), $$ P\left\\{X_{(k)}-X_{(k-1)}>t\right\\}=(1-t)^{n} $$ where \(X_{0} \equiv 0, X_{n+1} \equiv t\).
What do you think about this solution?
We value your feedback to improve our textbook solutions.