What Is the Probability Distribution Function After Four Steps in a Random Walk?

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Homework Help Overview

The discussion revolves around a random walk problem where a particle moves along the x-axis, starting at 0, and takes four steps either to the left or right with equal probability. Participants are exploring the probability distribution function (pdf) of the particle's position after these steps, particularly focusing on the implications of the binomial distribution in this context.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants are examining the relationship between the number of steps taken in one direction and the resulting position on the x-axis. There are questions about how to correctly apply the binomial distribution to determine the pdf, particularly regarding the interpretation of the variable k and its relation to possible outcomes.

Discussion Status

There is an active exploration of the problem, with participants questioning the initial application of the binomial formula and discussing how to correctly represent the outcomes based on the number of steps. Some participants suggest that the original approach needs adjustment to account for the relationship between k and the final position, indicating a productive direction in the discussion.

Contextual Notes

Participants note that the outcomes are constrained by the number of steps, leading to only certain positions being possible after an even number of steps. There is also mention of the need for k to be defined appropriately to avoid negative values, which adds complexity to the application of the binomial distribution.

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Homework Statement


Suppose a particle moves along the x-axis beginning at 0. It moves one integer step to the left or right with equal probability. What is the pdf of its position after four steps?

2. Homework Equations

Binomial distribution
##P(k) = {{n}\choose{k}} p^k (1-p)^{n-k}##

The Attempt at a Solution


In this case, ##p=0.5## and ##n=4##, so
##P(k) = {{4}\choose{k}}\frac{1}{16}##

But this is intuitively wrong, as ##P(0)## should be maximum, but here ##P(0) = \frac{1}{16}##. What am I missing here? Thank you.
 
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I think you are on the right track, but:

What are the possible outcomes?

What does k stand for? And how does it relate to the possible outcomes?
 
That's is not exactly the right formula. How do you plug in negative numbers to it? For 4 steps, it is easy enough to work out by hand what the probability of each outcome is. You should start to see a pattern after doing 3 or 4 steps.
 
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That's true scott, but if there were more steps, that would become harder.
His basic idea is sound, so long as he applies it correctly. Then he will be able to use the maths to quickly answer bigger cases.
 
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Merlin3189 said:
That's true scott, but if there were more steps, that would become harder.
His basic idea is sound, so long as he applies it correctly. Then he will be able to use the maths to quickly answer bigger cases.
Yes, but how do you plug in ##{{4}\choose{k}}## when k is negative?
And it needs to account for "missing numbers", like on even turns, only even outcomes are possible. On odd turns, you can only have odd results.
That's what I meant about the formula is not exactly right. You need to somehow get k to be from 0 to n, and have a formula of how that k relates to the actual number results.
 
Outcomes are [-4,4].

The variable k is the number of successes. Let's define success as +1 on the x axis.

The relation between k and the outcomes...

k=0 gives the outcome -4,
k=1 gives the outcome -2,
k=2 gives the outcome 0,
k=3 gives the outcome 2,
k=4 gives the outcome 4.

So ##P(w) = P(2k-4)##?
 
Well you don't plug negative numbers into k.
k does not represent the position on the line. It represents something else, which maps to positions.

If you take a more common situation where we use binomial distribution to calculate the probability of outcomes, like rolling a dice, ## P(3)= {{n}\choose{k}} p^k (1-p)^{n-k} = {{4}\choose{3}} (\frac 1 6)^3 (1-\frac 1 6)^{4-3}## , does not represent the probability of rolling a 3 in 4 tries, rather the probability that out of 4 tries you will get your chosen number 3 times.
 
showzen said:

Homework Statement


Suppose a particle moves along the x-axis beginning at 0. It moves one integer step to the left or right with equal probability. What is the pdf of its position after four steps?

2. Homework Equations

Binomial distribution
##P(k) = {{n}\choose{k}} p^k (1-p)^{n-k}##

The Attempt at a Solution


In this case, ##p=0.5## and ##n=4##, so
##P(k) = {{4}\choose{k}}\frac{1}{16}##

But this is intuitively wrong, as ##P(0)## should be maximum, but here ##P(0) = \frac{1}{16}##. What am I missing here? Thank you.

The binomial distribution is the distribution of the number of positive steps, not the distribution of the final position.
 
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Yes, I'd be happy with that. I might choose to say it a little differently, but then I'm always a bit verbose!
showzen said:
Outcomes are [-4,4].

The variable k is the number of successes. Let's define success as +1 on the x axis. Yes

The relation between k and the outcomes... Yes

k=0 gives the outcome -4,
k=1 gives the outcome -2,
k=2 gives the outcome 0,
k=3 gives the outcome 2,
k=4 gives the outcome 4.

So ##P(w) = P(2k-4)##?
I guess w is the outcome in the list. So w=2k-4 and k = (4+w)/2
So ## P(ending \ at \ w) = {{n}\choose{k}} p^k (1-p)^{n-k} \ where \ k = \frac {(4+w)} {2} ##

And actually I'm regretting my careless use of the word "outcomes", because I think Ray's use for the number of positive steps is more appropriate.
 
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Merlin3189 said:
Yes, I'd be happy with that. I might choose to say it a little differently, but then I'm always a bit verbose!

So ## P(ending \ at \ w) = {{n}\choose{k}} p^k (1-p)^{n-k} \ where \ k = \frac {(4+w)} {2} ##

And actually I'm regretting my careless use of the word "outcomes", because I think Ray's use for the number of positive steps is more appropriate.

This problem had 4 steps with equal probability. So in general with ##n## steps and ##p## probability, we have ## P(ending \ at \ w) = {{n}\choose{k}} p^k (1-p)^{n-k} \ where \ k = \frac {(n+w)} {2} ##?
 
  • #11
showzen said:
This problem had 4 steps with equal probability. So in general with ##n## steps and ##p## probability, we have ## P(ending \ at \ w) = {{n}\choose{k}} p^k (1-p)^{n-k} \ where \ k = \frac {(n+w)} {2} ##?
Yes, as long as n+w is even.
If it takes k steps in the w direction from the origin then it takes n-k steps the other way. To end at w we need k-(k-n)=w. The k towards w can be any of the n.
 

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