Principle Components Analysis: Variation

#1
Why do you choose the two factors with the highest proportion of variance to use in an analysis? Wouldn't a higher proportion of variance imply less correlation?
 

gianmarco

TS Contributor
#2
Hi!
Just wondering where this statement of yours comes from:
Wouldn't a higher proportion of variance imply less correlation?
I am not very familiar with PCA, but since it has some things in common with other scaling tecniques (e.g., multidimensional scaling, correspondence analysis, and the like) I think that I know something on how it works in general. So, I think you are confounding data variability (variance) with correlation between factors, or even correlation between factors and variables.....
In my opinion.

Regards
Gm
 
#3
hi can u plz tell me. as i am management student and not strong in econometrics.... kindly if u can reply my question...would be appretiabale .

i have one variable as dependent the corporate scial responsibility. i operationalized it and produce five dimensions. and each dimension have atleast 3 items and these items are taken tone valie eiterh o or 1 . then its avergae define the particular dimension of CSR . my independent variable is meaured from formula. so i have one variable to be analsed. can i run fator analysis plzzzzzzzzzzzz tell me