CLASSIFICATION STATISTIC PLOTName:
The classification statistic plot reverses the role of the reponse variable and the factor variables. For the classification statistic plot, the Y axis variable is assumed to be qualitative (i.e., a specific number of levels) and the factor variables are assumed to be continuous (the plot will still work if some of the factor variables are also qualitative). The context is the common classification problem where we use the values of the factor variables to classify which group an observation belongs to.
For this plot, the subplots are based on the distinct levels of the response variable. For example, suppose the Y axis variable (Y) has two possible values. Then for the first factor variable (X1), we plot the values of X1 corresponding to Y = 1 with x-coordinate 0.8 and the we plot the values of X1 corresponding to Y = 2 with x-coordinate 1.2. A similar subplot is created for each factor variable.
Although this plot can be generated with any univariate statistic supported by Dataplot, it is most typically used for a location statistic such as the mean or the median.
This plot graphically shows the following:
where <y> is the (qualitative) response variable;
<x1> ... <xk> is a list of 1 to k factor variables;
<stat> is the desired statistic;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.
CLASSIFICATION MEAN PLOT Y X1 TO X8
CLASSIFICATION MEDIAN PLOT Y X1 X2
CLASSIFICATION SD PLOT Y X1 X2 X3
Only statistics based on a single response variable are available with the CLASSIFICATIONS STATISTIC PLOT.
case asis title case asis label case asis title offset 2 set write decimals 3 . . Step 1: Read the data . SKIP 25 READ IRIS.DAT X1 TO X4 Y SKIP 0 . . Step 2: Set plot control features . CHARACTERS X BLANK LINES SOLID SOLID LET NFACT = 4 XLIMITS 1 NFACT MAJOR XTIC MARK NUMBER NFACT MINOR XTIC MARK NUMBER 0 TIC MARK OFFSET UNITS DATA XTIC OFFSET 1 1 XTIC LABEL FORMAT ALPHA XTIC LABEL CONTENT 1sp()2sp()3cr()Sepalcr()Length 1sp()2sp()3cr()Sepalcr()Width ... 1sp()2sp()3cr()Petalcr()Length 1sp()2sp()3cr()Petalcr()Width X1LABEL DISPLACEMENT 15 X1LABEL FACTORS . . Step 3: Generate plots . TITLE Classification Mean Plot CLASSIFICATION MEAN PLOT Y X1 X2 X3 X4