Question about Independent Random Variables and iid

Click For Summary
The discussion centers on the confusion regarding the independence of identically distributed random variables derived from a fair coin flip. It establishes that the random variable X assigns values based on coin outcomes, with X(H)=1 and X(T)=-1. The participant mistakenly calculates the joint probability P(X1=1, X2=1) as 1/2 instead of the correct value of 1/4, which arises from misunderstanding the sample space for two flips. The correct sample space includes four outcomes, leading to the conclusion that the probabilities must reflect this structure. Clarification is sought on the nature of independence and the calculation of joint probabilities.
chingkui
Messages
178
Reaction score
2
I have a question about independent random variable:
Let say we flip a fair coin, the set of outcome is S={H,T}, P(H)=1/2, P(T)=1/2. Define random variable X:S->R by X(H)=1, X(T)=-1.
From what I read in books, I can define X1 and X2 as independent identically distributed (iid) random variables with the same distribution as X. Then, that would mean P(X1=1,X2=1)=P(X1=1)P(X2=1).
It can easily be seen that the event {X1=1,X2=1}={w in S:X1(w)=1,X2(w)=1}={w in S:w=H}={w in S:X1(w)=1}={X1=1}={w in S:X2(w)=1}={X2=1}, and since P({w:w=H})=P(H)=1/2, we have P(X1=1,X2=1)=1/2 and P(X1=1)P(X2=1)=1/4.
So, I am not sure exactly what I mistake I made. Please help me clear up my confusion. Thanks.
 
Physics news on Phys.org
The sample space (S) for two flips has four points (H,H), (H,T), (T,H), (T,T), each of which has probability 1/4. In abstract terms, the sample space for n independent random variables is the direct product of the sample spaces of each of the variables.
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

Similar threads

  • · Replies 54 ·
2
Replies
54
Views
6K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 30 ·
2
Replies
30
Views
4K
  • · Replies 5 ·
Replies
5
Views
2K