Quant - must know

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BaseballRedhawks

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So quant is something that i’ve always sucked at. i’m just glad that we dont have to deal with z, t, or any of the tables anymore.
It seems like the thing that we MUSt know is:
http://en.wikipedia.org/wiki/68–95–99.7_rule
1 standard deviaiton from the mean is 68%…..
2 standard deviations from the mean is 95%
3 standard deivaitons from the mean is 99%.
Is there anything else that it is highly recommended (form levels 1 and 2/common sense)?
Thanks!
 
you still need to remember the more common z values for calculation of VAR. you would be set with remembering what the z value is for .01, .05, and .1 probability values for the data under the normal distribution.
not to mention that you’ll also have to deal with hypothesis testing in R32.
Stats topics are considerably easier compared to L2.
 
Also help to keep in mind what returns are normally distributed versus those that are not.
 
Thanks and:
Null hypothesis = Managers add no value.
Type 1 error is rejecting a true null hypothesis; retaining useless managers
Type 2 error is fialing to reject a false null hypothesis. firing managers who add value.
 
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