Probability Theory 2: Finding Mean and Variance of X_n on Real Line

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Discussion Overview

The discussion revolves around the problem of finding the mean and variance of a random variable X_n representing the position of an individual traveling on the real line after n steps, where each step has a mean of 0 and a variance dependent on the square of the current position. The scope includes mathematical reasoning and variance definitions.

Discussion Character

  • Mathematical reasoning
  • Homework-related
  • Technical explanation

Main Points Raised

  • One participant expresses confusion about how to start the problem and seeks suggestions.
  • Another participant clarifies the movement description, suggesting a correction in the wording regarding the mean of the next position.
  • A participant asserts that the answer for part a is straightforward, claiming it is given in the problem statement.
  • One participant proposes that E[X_n] = 0 based on the mean of each step being 0.
  • Another participant questions how to derive the variance for X_n from the variance definition, indicating uncertainty about the relationship between X and X_n.
  • One participant suggests that the variance remains constant as bX^2 for each step.
  • Another participant counters that the variance changes with each step, prompting a discussion about the mapping of variance from X_n to its squared form.
  • A participant confirms that the variance for X_n is indeed bX_n^2.

Areas of Agreement / Disagreement

Participants generally agree on the mean being 0 for E[X_n], but there is disagreement regarding the behavior of variance across steps, with some asserting it remains constant while others argue it changes.

Contextual Notes

Participants express uncertainty about the implications of the variance definition and its application to the problem, particularly regarding the dependence on previous steps.

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An individual traveling on the real line is trying to reach the origin. However, the larger the desired step, the greater is the variance in the result of that step. Specifically, whenever the person is at location x, he next moves to a location having mean 0 and variance [tex]\beta x^2[/tex]. Let [tex]X_n[/tex] denote the position of the individual after having taken n steps. Supposing that [tex]X_0 = x_0[/tex], find
a. [tex]E[X_n][/tex]
b. [tex]Var(X_n)[/tex].

I am not sure how to even start this problem, and would really appreciate any suggestions!
 
Last edited:
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Did you mean:

"whenever the person is at location xn, he next moves to a location xn+1 with error having mean 0"?
 
Last edited:
No, I copied exactly what the book said. I'm so confused!
 
Okay. Part a is easy. The problem gives away the answer. (The answer is stated unambiguously as part of the problem statement.)

For part b, what does the definition of variance say? (E.g. Var[x] = b x^2.)
 
Okay, so for part a, E[Xn] = 0 because with every step the mean is 0...right?

For part b.. I'm still not sure.
I know Var(X) = bx^2, but I don't know how to get from X to Xn. I tried using the definition of variance: E[X^2] - (E[X])^2 but it didn't get me very far
 
I know Var(X) = bx^2, but I don't know how to get from X to Xn.
The question is, if you know Xn, do you need to know X0, ..., X(n-1) to know Var(Xn)?
 
The variance is the same for each step that he takes, so why wouldn't the variance just still be bx^2?
 
No, the variance changes with each step, unless you happen to stay where you are (which is highly improbable). Look at the definition of the variance. It maps x to bx^2. Suppose Xn = t. Where does it map t?
 
bXn^2 ?
 
  • #10
Yes.
 

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