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As far as I understood, R squared explains how much the variation in Y is explained by its linear association with X. And it's used as an indicator for goodness of fit of a linear model.

Then when should I use r (Pearson coefficient)? How is it useful?

denis631
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    Flagged this as a duplicate. I arbitrarily chose one possible question it duplicates but there are many. Have a look, OP. http://stats.stackexchange.com/questions/13314/is-r2-useful-or-dangerous ... http://stats.stackexchange.com/questions/29713/what-is-covariance-in-plain-language ... http://stats.stackexchange.com/questions/26300/does-causation-imply-correlation ... http://stats.stackexchange.com/questions/221936/does-no-correlation-imply-no-causality ... http://stats.stackexchange.com/questions/534/under-what-conditions-does-correlation-imply-causation ... – gammer Mar 26 '17 at 17:07
  • @gammer much appreciated! – denis631 Mar 26 '17 at 17:08

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