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May 23, 2024 at 4:28 comment added rubikscube09 For anyone seeing this - this is also known as the Lindeberg swapping argument!
May 16, 2020 at 23:41 history edited jlewk CC BY-SA 4.0
typos
Mar 21, 2020 at 23:49 comment added Eric Auld Really great answer. I find this much more intuitive than characteristic function kung-fu.
Apr 25, 2019 at 2:43 history edited jlewk CC BY-SA 4.0
More to the point
Mar 22, 2019 at 3:10 history edited jlewk CC BY-SA 4.0
typo
Mar 19, 2019 at 23:45 history edited jlewk CC BY-SA 4.0
typo
S Mar 19, 2019 at 20:40 history edited jlewk CC BY-SA 4.0
some MathJax editing, mostly \ldots and \cdots
S Mar 19, 2019 at 20:40 history suggested CommunityBot CC BY-SA 4.0
some MathJax editing, mostly \ldots and \cdots
Mar 19, 2019 at 20:27 review Suggested edits
S Mar 19, 2019 at 20:40
Mar 19, 2019 at 19:50 history edited jlewk CC BY-SA 4.0
Some typos/better looking fractions
Mar 19, 2019 at 16:53 history edited jlewk CC BY-SA 4.0
typo
Mar 15, 2019 at 22:28 history edited jlewk CC BY-SA 4.0
Add outline and fix formatting
Mar 15, 2019 at 19:57 history edited jlewk CC BY-SA 4.0
Add relationship to the more typical statement of the CLT
Mar 14, 2019 at 18:23 comment added whuber I see what you mean. What gives me pause is that your assertion concerns only expectations and not distributions, whereas the CLT draws conclusions about a limiting distribution. The equivalence between the two might not immediately be evident to many. Might I suggest, then, that you provide an explicit connection between your statement and the usual statements of the CLT in terms of limiting distributions? (+1 by the way: thank you for elaborating this argument.)
Mar 14, 2019 at 16:09 comment added jlewk I am not sure why you would say this, @whuber. The above give an intuitive proof that $E[f((X_1+...+X_n)/\sqrt n)]$ converges to $E[f(Z)]$ where $Z\sim N(0,1)$ for a large class of functions $f$. This is the CLT.
Mar 14, 2019 at 14:59 comment added whuber You seem to be asserting a law of large numbers rather than the CLT.
Mar 14, 2019 at 7:25 review Late answers
Mar 14, 2019 at 7:27
Mar 14, 2019 at 7:08 history answered jlewk CC BY-SA 4.0