SUM OF SQUARES

SUM OF SQUARES (LET)

Let Subcommand

Compute the sum of squares of a variable.

The sum of squares has the formula:
\( \mbox{SSQ} = \sum_{i=1}^{N}{X_{i}^2} \)

You can also compute the difference of the sum of squares between two response variables. That is, compute the sum of squares for each variable and then compute the difference between these two values.

LET <par> = SUM OF SQUARES <y>
                        <SUBSET/EXCEPT/FOR qualification>
where <y> is the response variable;
            <par> is a parameter where the computed sum of squares is saved;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

LET <par> = DIFFERENCE OF SUM OF SQUARES <y1> <y2>
                        <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 is saved;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

This syntax computes the sum of squares of <y1> and <y2> and then computes the difference of the two sum of squares values.

LET A = SUM OF SQUARES Y1
LET A = SUM OF SQUARES Y1 SUBSET TAG > 2
LET A = DIFFERENCE OF SUM OF SQUARES Y1 Y2

In some applications it may be desired to cap the value of outliers. This is most common when the response variable is a z-score or some other standardized score. To specify this value, enter the command
LET CAPVALUE = <value>

where <value> is typically 3 or 4 (if the reponse data are z-scores or z-score type data). Note that the value represents an absolute value. For example, if CAPVALUE is 4, values greater than 4 will be set to 4 and values less than -4 will be set to -4.

Dataplot statistics can be used in a number of commands. For details, enter
HELP STATISTICS

None

SSQ is a synonym for SUM OF SQUARES

MEAN	= Compute the mean of a variable.
STANDARD DEVIATION	= Compute the standard deviation of a variable.
ROOT MEAN SQUARE	= Compute the root mean square error of a variable.

Statistics

2012/2
2012/6: Added DIFFERENCE OF SUM OF SQUARES

 
LET Y1 = NORMAL RANDOM NUMBERS FOR I = 1 1 100
LET SSQ = SUM OF SQUARES Y1
    

The resulting value is 85.67012.