Conditional expectation in statistics

In summary, the conversation discusses the relationship between E[W|X] and Cov(W,X) and whether the statement "if E[W|X]=0, then Cov(W,X)=0" is true. The difficulty lies in the fact that this statement is not always true, but it is true if E[W|X] is equal to E[W]. The conversation also explores the use of conditional expectation and the question of whether the expected value of two variables, WX, can be conditioned on X and then X extracted.
  • #1
libragirl79
31
0
Hi,

I am trying to show that if the E[W|X]=0 then the Cov (W,X)=0.




Using the def of variance, and given that E[W] is zero,
I get that Cov is equal to: E[WX]-E[W * E(X)]

using conditional expectation:

E [E(WX|X)] -E[x]E[W]= E[X E[W|X]]-E[X]E[E(W|X)]=0

I am not sure if this transition (in red) is ok.

Thanks!
 
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  • #2
libragirl79 said:
Hi,

I am trying to show that if the E[W|X]=0 then the Cov (W,X)=0.
The difficulty is that this statement is, in general, NOT true.
What is true is that if E[W|X]= E[W] then Cov(W, X)= 0.



Using the def of variance, and given that E[W] is zero,
What? Where is that gven?

I get that Cov is equal to: E[WX]-E[W * E(X)]

using conditional expectation:

E [E(WX|X)] -E[x]E[W]= E[X E[W|X]]-E[X]E[E(W|X)]=0

I am not sure if this transition (in red) is ok.

Thanks!
 
  • #3
Thanks for the reply!

From what I understand the posed statement is true when E[W|X]=0 a.s.

E[W]=E[E[W|X]]=E[0]=0 and the def of cov being E[(W-E(W))(X-E(X))]

The question I have is if Expec value of two vars, WX, can be conditioned as I wrote above on X and then X extracted...
 
  • #4
libragirl79 said:
Thanks for the reply!

From what I understand the posed statement is true when E[W|X]=0 a.s.

E[W]=E[E[W|X]]=E[0]=0 and the def of cov being E[(W-E(W))(X-E(X))]

The question I have is if Expec value of two vars, WX, can be conditioned as I wrote above on X and then X extracted...

Cov(W,X) = E(W*X) - EW * EX (a standard result). Can you relate E(W*X) and EW to E(W|X)?
 
  • #5
The only way I know how to relate the two was by doing the conditioning I did of both WX on X...It would be optimal if W and X were indep, then the stand result for Cov works perfectly, but that's not the case here...
 

Related to Conditional expectation in statistics

1. What is conditional expectation in statistics?

Conditional expectation in statistics is a measure of the expected value of a random variable given the knowledge of another random variable. It is a way to calculate the average outcome of a random variable, taking into account a specific condition or event that has already occurred.

2. How is conditional expectation calculated?

Conditional expectation can be calculated using a formula that takes into account the probability of the condition and the expected value of the random variable given that condition. This formula is often written as E[X|Y], where X is the random variable and Y is the condition.

3. What is the difference between unconditional and conditional expectation?

The unconditional expectation is the average value of a random variable without taking any specific conditions into account. On the other hand, conditional expectation takes into account a specific condition or event that has occurred, and calculates the average value of the random variable based on this condition.

4. How is conditional expectation used in data analysis?

Conditional expectation is a useful tool in data analysis as it allows for a more accurate prediction of outcomes by taking into account specific conditions or events. It is often used in regression analysis to estimate the relationship between two variables and to make predictions based on this relationship.

5. What are some real-life applications of conditional expectation in statistics?

Conditional expectation has many practical applications in various fields, such as economics, finance, and engineering. For example, it can be used in predicting stock prices based on market conditions, estimating the probability of default on a loan, or determining the expected lifespan of a product based on its usage. It is also used in risk analysis and decision-making processes.

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