Hi, A have small technical question about the calculation of R-squared using lm(). In a study case with experimental values, it seems more logical to force the regression line to pass through origin with lm(y ~ x +0). However, R-squared values are higher in this case than when I compute the linear regression with lm(y ~ x). It seems to be surprising to me: is this result normal ? Is there any problem in the R-squared value calculated in this case ? Thanks, Etienne Toffin
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