Expected values of random variables

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sid9221
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I don't completely understand why the area of the proof circled in red is true.

Any advice would be appreciated.

https://dl.dropboxusercontent.com/u/33103477/Q1.jpg
 
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Office_Shredder said:
X1 is a random variable whose mean is [itex]\mu[/itex] by definition. Can you elaborate on your confusion?

Where is this defined ? Is is part of the definition of 'Expectation' ?
 
Office_Shredder said:
Why don't you tell us what you think X1 is, and what [itex]\mu[/itex] is, and we can work from there.

μ=[itex]\frac{\sum X_i}{N}[/itex]

[itex]x_1[/itex] is just a variable
 
sid9221 said:
μ=[itex]\frac{\sum X_i}{N}[/itex]

No, the thing on the right hand side is [itex]\overline{X}[/itex], not [itex]\mu[/itex]. To give an example, suppose I flip ten coins, and assign a value of 1 to a heads, and 0 to a tails. I might get the following:

1,0,0,1,0,0,1,0,1,0.

[itex]\mu[/itex] in this context is the expected value of a single flip of the coin, which is .5. [itex]\overline{X}[/itex] is the average of the flips I actually made, which is .4. X1 is the value of the first flip, which in this case happens to be 1, but hopefully it's clear that E(X1) = .5 before I actually flip the coin since X1 is just an arbitrary flip of the coin.