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 - 11/5/14
 
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Hey guys,
One of the standard results in elementary stochastic calculus is that, if [imath]X[/imath] is a random variable, and [imath]Y[/imath] is any square integrable random variable, then the conditional expectation [imath]\mathbb{E}[Y|X][/imath] exists and is unique. I am struggling to understand a particular step (inequality) in the first part of the proof, where the author proves that [imath]W=g(X)[/imath] and [imath](Y-Y^{\star})[/imath] are orthogonal. I have posted this as a question on MSE here.
I have tried searching the proof online, but the approach in my text appears a bit different. I would really benefit from any suggestions/clues with it.
Cheers,
Quasar
	
		
			
		
		
	
				
			One of the standard results in elementary stochastic calculus is that, if [imath]X[/imath] is a random variable, and [imath]Y[/imath] is any square integrable random variable, then the conditional expectation [imath]\mathbb{E}[Y|X][/imath] exists and is unique. I am struggling to understand a particular step (inequality) in the first part of the proof, where the author proves that [imath]W=g(X)[/imath] and [imath](Y-Y^{\star})[/imath] are orthogonal. I have posted this as a question on MSE here.
I have tried searching the proof online, but the approach in my text appears a bit different. I would really benefit from any suggestions/clues with it.
Cheers,
Quasar