Understanding the Variance of a One-Dimensional Random Walk

In summary, the conversation discusses the expectation and variance for a one-dimensional simple random walk. It is stated that the expectation is zero and the variance is equal to the number of steps taken. The conversation also includes a proof of this statement by using the definition of S_n and the independence of the variables.
  • #1
grad
12
0
Hi,

I know that the expectation E(Sn) for a one-dimensional simple random walk is zero. But what about the variance?

I read in http://en.wikipedia.org/wiki/Random_walk#One-dimensional_random_walk" that the variance should be E(Sn2) = n.

Why is that? Can anyone prove it?

Thank you very much!
 
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  • #2
Just write down the definition of [itex]S_n[/itex] and you will be able to answer your question yourself.
 
  • #3
Var(Sn) = E(Sn2) = E(Z12 + Z22 + Z32 + ... + Zn2) =* E(Z12) + E(Z22) + ... + E(Zn2) = 1 + 1 + ... + 1 (n times) = n

*variables are independent and uncorrelated

Is this correct then?
 
  • #4
This is almost correct. [itex]S_n[/itex] is defined to be [itex]Z_1+\ldots +Z_n[/itex], where the [itex]Z_i[/itex] are independent (or at least uncorrelated) with mean zero and variance one. It follows that
[tex]
S_n^2 = \sum_{i,j=1}^n{Z_i Z_j}
[/tex]
and not, as you wrote,
[tex]
S_n^2 = \sum_{i=1}^n{Z_i^2}
[/tex]

However, using independence of the [itex]Z_i[/itex] you can still do a similar computation to prove [tex]\mathbb{E}\left[S_n^2\right]=n[/tex].
 
  • #5
Thank you!
 
  • #6
You're welcome:smile:
 

FAQ: Understanding the Variance of a One-Dimensional Random Walk

What is a random walk and how does variance play a role?

A random walk is a mathematical concept that describes the movement of an object that takes random steps in a particular direction. Variance in a random walk refers to the measure of how much the object deviates from its expected or average position over time. It helps to quantify the uncertainty and randomness involved in the movement of the object.

How is variance calculated in a random walk?

Variance in a random walk is calculated by finding the average of the squared differences between each step and the expected position. This is known as the mean squared displacement. Mathematically, it can be represented as Var(X) = E[(X - μ)^2], where X is the position of the object at a given time, μ is the expected position, and E is the expected value or average.

What factors can affect the variance in a random walk?

The variance in a random walk can be affected by several factors, such as the size of the steps taken, the direction of the steps, the starting position, and the number of steps taken. These factors can influence the randomness and uncertainty in the movement of the object, thus affecting the variance.

How does variance change over time in a random walk?

In a random walk, the variance typically increases over time as the object takes more steps and moves further away from its starting position. This is because the more steps taken, the higher the chance of the object deviating from its expected position and the larger the spread of its possible positions.

What are some real-world applications of variance in random walks?

Variance in random walks has various applications in fields such as finance, biology, physics, and computer science. In finance, it is used to model the stock market and predict stock prices. In biology, it is used to study the movement of animals and cells. In physics, it is used to model the diffusion of particles. In computer science, it is used in algorithms for data analysis and image processing.

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