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

In summary: So there is a ##{{n}\choose{k}}## ways to do it out of 2n possible ways. So the probability is ## \frac {{n}\choose{k}}{2n} ####P(w) = P(ending \ at \ w) = \frac {{n}\choose{k}}{2n}##?Yes, so long as n+w is even.In summary, we can use the binomial distribution to calculate the probability of a particle ending at a certain position along the x-axis after a given number of steps. The formula is P(w) = P(ending at w) = (n choose k)/(2n), where n is the number of steps and k is the number
  • #1
showzen
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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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  • #2
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?
 
  • #3
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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  • #4
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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  • #5
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.
 
  • #6
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)##?
 
  • #7
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.
 
  • #8
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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  • #9
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.
 
  • #10
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.
 

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

What is a random walk in 1 dimension?

A random walk in 1 dimension is a mathematical concept that describes the movement of a point or particle in a straight line, where the direction of each step is randomly determined. This concept is often used in statistical physics and can be used to model various phenomena such as diffusion and Brownian motion.

What is the difference between a random walk and a random process?

A random walk is a specific type of random process where the outcome of each step is determined by a random element. However, not all random processes involve movement or steps, as some may involve random changes in a quantity or variable over time.

How is a random walk in 1 dimension simulated?

A random walk in 1 dimension can be simulated using a computer program or by physically performing the steps with a coin flip or dice roll. In a computer program, a random number generator is used to determine the direction of each step. In physical simulations, a coin flip or dice roll can be used to determine the direction of each step.

What are some real-life applications of random walks in 1 dimension?

Random walks in 1 dimension have various applications in different fields such as finance, physics, biology, and computer science. For example, it can be used to model the movement of stock prices, the diffusion of particles in a liquid, the movement of molecules in a gas, and the behavior of animals searching for food.

What are the limitations of using a random walk in 1 dimension to model real-life phenomena?

One limitation of using a random walk in 1 dimension is that it assumes equal probabilities for each step, which may not always be the case in real-life situations. Additionally, it does not take into account external factors or obstacles that may affect the movement of particles or objects. It is also a simplified model and may not fully capture the complexity of real-life phenomena.

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