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DIFFERENCE OF AADName:
with \( \bar{x} \) denoting the mean of the variable and n denoting the number of observations. This statistic is sometimes used as an alternative to the standard deviation. For the difference of average absolute deviations, the average absolute deviation is computed for each of two samples then their difference is taken.
where <y1> is the first response variable; <y2> is the first response variable; <par> is a parameter where the computed difference of the average absolute deviations is stored; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
LET A = DIFFERENCE OF AAD Y1 Y2 SUBSET X > 1
to compute differences from the median. Since the DIFFERENCE OF AVERAGE ABSOLUTE DEVIATIONS was based on the average absolute deviation computation, these changes apply to it as well.
SKIP 25
READ IRIS.DAT Y1 TO Y4 X
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LET A = DIFFERENCE OF AAD Y1 Y2
TABULATE DIFFERENCE OF AAD Y1 Y2 X
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XTIC OFFSET 0.2 0.2
X1LABEL GROUP ID
Y1LABEL DIFFERENCE OF AAD
CHAR X
LINE BLANK
DIFFERENCE OF AAD PLOT Y1 Y2 X
CHAR X ALL
LINE BLANK ALL
BOOTSTRAP DIFFERENCE OF AAD PLOT Y1 Y2 X
Dataplot generated the following output.
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** LET A = DIFFERENCE OF AAD Y1 Y2 **
***************************************
THE COMPUTED VALUE OF THE CONSTANT A = 0.35400003E+00
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** TABULATE DIFFERENCE OF AAD Y1 Y2 X **
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* Y1 AND Y2
X * DIFFERENCE OF AVERAGE ABSOLUTE
**********************************************
1.00000 * -0.140000E-01
2.00000 * 0.170000
3.00000 * 0.254000
GROUP-ID AND STATISTIC WRITTEN TO FILE DPST1F.DAT
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Date created: 03/27/2003 | ||||||||||||||||||||||