If we want to relate a random variable y to two-independent variables and , a regression hyperplane is the three-dimensional equivalent of a regression line that minimizes the sum of the squared vertical deviations between the sample points suspended in y vs. vs. space and their associated multiple regression estimates, all of which lie on this hyperplane.

Question

If we want to relate a random variable y to two-independent variables  and  , a regression hyperplane is the three-dimensional equivalent of a regression line that minimizes the sum of the squared vertical deviations between the sample points suspended in y vs.  vs.  space and their associated multiple regression estimates, all of which lie on this hyperplane.

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The Answer of If we want to relate a random variable y to two-independent variables  and  , a regression hyperplane is the three-dimensional equivalent of a regression line that minimizes the sum of the squared vertical deviations between the sample points suspended in y vs.  vs.  space and their associated multiple regression estimates, all of which lie on this hyperplane.

If We Want to Relate a Random Variable Y to Two-Independent