
SUM OF SQUARES FROM MEANName:
with \( \bar{X} \) denoting the mean of the X_{i}. You can also compute the difference of the sum of squares from the mean between two response variables. That is, compute the sum of squares from the mean for each variable and then compute the difference between these two values.
<SUBSET/EXCEPT/FOR qualification> where <y> is the response variable; <par> is a parameter where the computed sum of squares from the mean is saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
<SUBSET/EXCEPT/FOR qualification> where <y1> is the first response variable; <y2> is the second response variable; <par> is a parameter where the computed difference of the sum of squares from the mean is saved; and where the <SUBSET/EXCEPT/FOR qualification> is optional. This syntax computes the sum of squares from the mean of <y1> and <y2> and then computes the difference of the two sum of squares values.
LET A = SUM OF SQUARES FROM MEAN Y1 SUBSET TAG > 2 LET A = DIFFERENCE OF SUM OF SQUARES FROM MEAN Y1 Y2
LET Y1 = NORMAL RANDOM NUMBERS FOR I = 1 1 100 LET Y1 = 10 + 5*Y1 LET SSQM = SUM OF SQUARES FROM MEAN Y1 SET WRITE DECIMALS 4 PRINT "Sum of Squares from Mean = ^SSQM"The following output is generated. Sum of Squares from Mean = 2136.114616  
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Date created: 03/08/2013 