Random Walk in 1D: Finding Average Steps to the Right After N Steps

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Homework Help Overview

The discussion revolves around a random walk in one dimension, where a person moves with defined probabilities to the left and right. The original poster attempts to find the average number of steps taken to the right after a specified number of steps, N, using a binomial distribution approach.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the formulation of the average steps to the right using binomial distribution, question the simplification of the summation, and explore the implications of limits as N approaches infinity.

Discussion Status

Some participants have provided insights into the relationship between the average and variance, while others are exploring the mathematical derivation of these concepts. There is an ongoing examination of the limits and conditions under which these formulas apply.

Contextual Notes

Participants note the need to consider the dependence of probabilities and the implications of large N on the variance and average calculations. There is also mention of homework deadlines influencing the urgency of the discussion.

ak416
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Random walk in one dimension. A person (say, in an unstable state of mind/body) is moving in
one dimension, with coordinate x, starting at x = 0. Assume: i.) that s/he moves in steps of length
l, ii.) that the probability that s/he takes a step to the left is p, while the probability of taking a
step to the right is q = 1 − p and iii.) that all the steps are independent (i.e. the probability of
taking the n + 1-th step left or right is independent on what the previous n steps were).

One of the questions ask: Find the average number of steps to the right, <nR>, taken after N steps.

This is what I got:
<nR> = sum i=0toN i*(N choose i) * p^(i) * (1-p)^(N-i)

A played around with it but i can't seem to get it into a nicer form. Other questions then ask for the variance and to compare it to the mean, so I am sure i have to somehow eliminate the summation sign. There's a hint saying to use the fact that p d/dp(p^n) = np^n. Is there a way to simplify this?
 
Last edited:
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Well, the way you set it up (if you're sure that's what the question is asking) that is just the mean of a binomial distribution with parameters N and p.
 
ya i know, i used the binomial distribution formula to come up with that formula. I think that's the best i can do. I have a better question. What is the limit as n approaches infinity? Because one of the other questions asks what the large N limit is for the ratio Var(nR) / <nR> . I managed to derive the formula for Var(nR) to be p*d/dp(<nR>) - <nR>^2 , so the limit I am looking for is (p*d/dp(<nR>))<nR> - <nR> , so as a start I would like to find the limit for large N of this <nR>. Anyone?
 
my guess is p * N but how do i derive that mathematically?
 
actually i think i messed up on the d/dp part, forgot to take into account that 1-p depends on p! If anyone can help me figure out a nice formula for the variance that would be great.
 
Well, it is p * N and the variance is Np(1 - p). John E. Freund's Mathematical Statistics gives proofs, but your book also probably does that. Never mind; I withdraw from this.
 
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Ya thanks, i was looking through my stats notes and saw the derivations. I am going to try finishing up the other problems now. Assignment is due in the morning!
 

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