Summation Simplification for Neumerator of Beta Estimator

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SUMMARY

The discussion focuses on simplifying the equation Ʃwixiyi - (ƩxiwiƩyiwi)/Ʃwi into the form Ʃ(something - something)yi. The correct simplification is identified as Ʃw_i(x_i - (Ʃ_j x_j w_j)/(Ʃ_k w_k)) y_i, where the term in brackets represents the deviation of x from its mean. The use of separate indices for each summation enhances clarity in the simplification process.

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LBJking123
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I need simplify this equation:

Ʃwixiyi - (ƩxiwiƩyiwi)/Ʃwi

Into an equation of the form: Ʃ(something - something)yi

I am pretty sure the first something is xiwi, but I have no idea what the second something would be...

Any help would be greatly appreciated. Thanks!
 
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LBJking123 said:
I need simplify this equation:

Ʃwixiyi - (ƩxiwiƩyiwi)/Ʃwi

Into an equation of the form: Ʃ(something - something)yi

I am pretty sure the first something is xiwi, but I have no idea what the second something would be...

Any help would be greatly appreciated. Thanks!

Come on, that's easy:
<br /> \sum_i w_i(x_i-\sum_j x_j w_j/\sum_k w_k) y_i<br />
Note that I chose a separate index for each summation for clarity.
The term in brakets is x minus <x>, i.e. the mean of x.
 
Ohhhhh I kept thinking it was going to be

Ʃ(xiwi-(xiwi2)/Ʃwi)yi

I makes more sense when you choose a separate index for each summation.

Thanks for the help DrDu!
 

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