Proof of variance for functions of variable

AI Thread Summary
The discussion centers on understanding the proof of theorem 4.3 related to variance in functions of random variables. A participant suggests applying definition 4.3 to the random variable Y=g(X) for clarity. Another contributor points out a potential omission in the original text, noting that the variance should be squared after the statement "It follows from Definition 4.3 that..." for better comprehension. This missing detail seems to hinder the understanding of theorem 4.3 and its proof. Clarifying this aspect may help others grasp the theorem more effectively.
georg gill
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http://bildr.no/view/1115383

i wonder if anyone could explain the proof for theorem 4.3 i have understood definition 4.3
 
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Hi Georg.
I don't know which is definition 4.1, but it doesn't matter.
If you take definition 4.3 and apply it to the random variable Y=g(X), you'll get it.
 
http://bildr.no/view/1115856

above is definition 4.1. In the first link that they have forgot to square the variance that appears after the text:

"It follows from Definition 4.3 that.." ?

If they would have done that I would have understood the theorem 4.3 and its proof
 
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