The proper conclusion is that the false smile is higher than the control and that the miserable smile is either The column labeled MS stands for "Mean Square" and therefore the value \(2.6489\) in the...The proper conclusion is that the false smile is higher than the control and that the miserable smile is either The column labeled MS stands for "Mean Square" and therefore the value \(2.6489\) in the "Error" row and the MS column is the "Mean Square Error" or MSE. Compute a Sum of Squares Error (\(SSE\)) using the following formula \[SSE=\sum (X-M_1)^2+\sum (X-M_2)^2+\cdots +\sum (X-M_k)^2\] where \(M_i\) is the mean of the \(i^{th}\) group and \(k\) is the number of groups.
The proper conclusion is that the false smile is higher than the control and that the miserable smile is either The column labeled MS stands for "Mean Square" and therefore the value \(2.6489\) in the...The proper conclusion is that the false smile is higher than the control and that the miserable smile is either The column labeled MS stands for "Mean Square" and therefore the value \(2.6489\) in the "Error" row and the MS column is the "Mean Square Error" or MSE. Compute a Sum of Squares Error (\(SSE\)) using the following formula \[SSE=\sum (X-M_1)^2+\sum (X-M_2)^2+\cdots +\sum (X-M_k)^2\] where \(M_i\) is the mean of the \(i^{th}\) group and \(k\) is the number of groups.
