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Suppose that a particle starts at the origin of the whole line and moves along the line in jumps of one unit. For each jump, the probability is p (0 ≤ p ≤ 1) that the particle will jump one unit to the left, and the probability is 1 − p that the particle will jump one unit to the right. Find the expected value of the position of the particle after n jumps

Short Answer

Expert verified

\(E\left( X \right) = {\left( {1 - 2p} \right)^n}\)

Step by step solution

01

Given information

A particle starts at the origin of the whole line and moves along the line in jumps of one unit.

For every jump, the chance is p (0 ≤ p ≤ 1) of the particle jumping one unit to the left is p (0 p 1), as well as the probability of the particle jumping one unit to the right, is 1 – p.

X is the random variable that takes two values -1 with probability p and 1 with probability 1-p.

02

Find E (X)

\(\begin{array}{c}E\left( X \right) = - 1 \times p + 1 \times \left( {1 - p} \right)\\ = 1 - 2p\end{array}\)

Step 3: Find the expected value of the position of the particle after n jumps

Let Y be the random variable where \(Y = {X_1}{X_2}...{X_n}\)\(\)

\(\begin{array}{c}Y = {X_1}{X_2}...{X_n}\\E\left( Y \right) = E\left( {{X_1}{X_2}...{X_n}} \right)\\\,\,\,\,\,\,\,\,\,\,\,\, = {\left( {1 - 2p} \right)^n}\,{\rm{as}}\,{X_1},{X_2},...{X_n}\,{\rm{are}}\,{\rm{independent}}\end{array}\)

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Most popular questions from this chapter

Prove the following extension of Theorem 4.4.1: If \(E\left( {{{\left| X \right|}^a}} \right) < \infty \) for some positive number a, then \(E\left( {{{\left| X \right|}^b}} \right) < \infty \) for every positive number \(b < a\). Give the proof for the case in which X has a discrete distribution.

Suppose that one word is to be selected at random from the sentence the girl put on her beautiful red hat. If X denotes the number of letters in the word that is selected, what is the value of E(X)?

For all numbers a and b such that \(a < b\), find the variance of the uniform distribution on the interval \(\left( {a,b} \right)\).

Suppose that a person has a given fortune\({\bf{A > 0}}\)and can bet any amount b of this fortune in a certain game\(\left( {{\bf{0}} \le {\bf{b}} \le {\bf{A}}} \right)\). If he wins the bet, then his fortune becomes\({\bf{A + b}}\); if he loses the bet, then his fortune becomes\({\bf{A - b}}\). In general, let X denote his fortune after he has won or lost. Assume that the probability of his winning is p\(\left( {{\bf{0 < p < 1}}} \right)\)and the probability of his losing is\({\bf{1 - p}}\). Assume also that his utility function, as a function of his final fortune x, is\({\bf{U}}\left( {\bf{x}} \right){\bf{ = logx}}\)for\({\bf{x > 0}}\). If the person wishes to bet an amount b for which the expected utility of his fortune\({\bf{E}}\left( {{\bf{U}}\left( {\bf{x}} \right)} \right)\)will be a maximum, what amount b should he bet?

Let X be a random variable with c.d.f F. Suppose that\(a < b\)are numbers such that both a and b are medians of X.

  1. Prove that\(F\left( a \right) = \frac{1}{2}\).
  2. Prove that there exists a smallest \(c \le a\)and a largest\(d \ge b\)such that every number in the closed interval\(\left( {c,d} \right)\) is a median of X.
  3. If X has a discrete distribution, prove that \(F\left( d \right) > \frac{1}{2}\).
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