Question about problem statement (marginal distribution)

  • Context: MHB 
  • Thread starter Thread starter kalish1
  • Start date Start date
  • Tags Tags
    Distribution
Click For Summary
SUMMARY

The forum discussion centers on a problem statement involving independent normal random variables $X$ and $Y$, both distributed as $N(\mu, \sigma^2)$. The user questions the relevance of a provided corollary for finding the marginal distributions of $X$ and $Y$. The corollary states that a linear combination of independent normal variables results in another normal variable, which is applicable here. The user also contemplates the marginal distributions of $U=X+Y$ and $V=X-Y$, indicating a misunderstanding of the marginal distributions concept.

PREREQUISITES
  • Understanding of normal distributions, specifically $N(\mu, \sigma^2)$
  • Knowledge of linear combinations of random variables
  • Familiarity with the concept of marginal distributions
  • Basic principles of independence in probability theory
NEXT STEPS
  • Study the properties of independent normal random variables
  • Learn about the Central Limit Theorem and its implications
  • Research the application of the corollary for linear combinations in probability
  • Explore examples of marginal distributions in multivariate normal distributions
USEFUL FOR

Students preparing for statistics exams, particularly those focusing on probability theory and normal distributions, as well as educators seeking to clarify concepts related to marginal distributions and independence in random variables.

kalish1
Messages
79
Reaction score
0
I am doing some problems from a practice final and would like to know if the following problem has mistakes in the way it is written. We are supposed to apply a corollary that doesn't seem to have any relevance in this context. It is throwing me off.

**Problem statement:** Suppose that $X$ ~ $N(\mu,\sigma^2)$ and $Y$ ~ $N(\mu,\sigma^2)$ and they are independent. Let $U=X+Y$ and $V=X+Y$. Use the following corollary to find the marginal distributions of $X$ and $Y$.

**Corollary:** Let $X_1, \ldots, X_n$ be mutually independent random variables with $X_i$ ~ $n(\mu_i, \sigma_i^2)$. Let $a_1, \ldots, a_n$ and $b_1, \ldots, b_n$ be fixed constants Then

$Z=\sum_{i=1}^n(a_iX_i + b_i)$ ~ $n(\sum_{i=1}^n(a_i\mu_i + b_i),\sum_{i=1}^na_i^2\sigma_i^2)$.

Also, aren't the marginal distributions of $X$ and $Y$ just $X$ and $Y$ themselves, because they are independent of each other??

Any help would be greatly appreciated. My final is tomorrow and I'm studying as hard as I can.
 
Physics news on Phys.org
I would guess that $$V= X - Y$$ and that you should find the find the marginal distributions of U and [FONT=MathJax_Math]V.

You should use the Corollary to find their distribution, then try and apply the marginal distribution stuff.

But I could be wrong, good luck!
 
Last edited:

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
Replies
1
Views
4K
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
Replies
16
Views
4K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
5
Views
5K
  • · Replies 2 ·
Replies
2
Views
2K