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The question appears to be simple enough, but i have two queries
A) does E[X1 X2] mean the same as E[X1  X2]
B) If not/so, how exactly do I go about computing this. I've seen a few formulas in my lectures notes for computing conditional expectations for discrete random variables,
however I find it difficult to understand and apply the notation/procedure.
Any help is appreciated!
edit: ok, after some more research, i've found that
E(X1 X2] simply means The expectations of X1 and X2 multiplied by each other.
so, what I want to ask now is this.
is the PMF of X1, given that table:
X1  1  0  1 
px(X1) 1/3  0  1/3 
And finally, how do i find out if X1 and X2 are independent?
EDIT 2: okay, is this correct
for E[X1 X2]
i do:
(1)(1)*(1/6) + ....
That is multiply each (X1,X2) and then multiply that by the probability of its occurrence, and add them all up?
The question appears to be simple enough, but i have two queries
A) does E[X1 X2] mean the same as E[X1  X2]
B) If not/so, how exactly do I go about computing this. I've seen a few formulas in my lectures notes for computing conditional expectations for discrete random variables,
however I find it difficult to understand and apply the notation/procedure.
Any help is appreciated!
edit: ok, after some more research, i've found that
E(X1 X2] simply means The expectations of X1 and X2 multiplied by each other.
so, what I want to ask now is this.
is the PMF of X1, given that table:
X1  1  0  1 
px(X1) 1/3  0  1/3 
And finally, how do i find out if X1 and X2 are independent?
EDIT 2: okay, is this correct
for E[X1 X2]
i do:
(1)(1)*(1/6) + ....
That is multiply each (X1,X2) and then multiply that by the probability of its occurrence, and add them all up?
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