Unlike the [[coefficient of determination]] in a regression involving just two variables, the coefficient of multiple determinationcorrelation is not computationally [[commutative]]: a regression of ''y'' on ''x'' and ''z'' will in general have a different R<sup>2</sup> than will a regression of ''z'' on ''x'' and ''y''. For example, suppose that in a particular sample the variable ''z'' is [[Correlation and dependence|uncorrelated]] with both ''x'' and ''y'', while ''x'' and ''y'' are linearly related to each other. Then a regression of ''z'' on ''y'' and ''x'' will yield an R<sup>2</sup> of zero, while a regression of ''y'' on ''x'' and ''z'' will yield a positive R<sup>2</sup>.