If you have more than one nominal or ordinal column selected in the Data Filter, this option clears any other selections before making a new selection. For example, using Big Class.jmp, suppose that you have the columns sex (nominal) and age (ordinal) in your Data Filter. If you have males (M) selected for sex, and you click on an age group, say age 12, your selection of males will be automatically cleared. This means that selecting age 12 is not conditional on selecting males. Conversely, if you turn off Auto clear, you can then select both males and age 12 at the same time. Auto clear is on by default.
The following example illustrates how the Conditional option helps show the subcategories clearly, without the extra categories that do not belong.
1.
Select Help > Sample Data Library and open Cities.jmp.
2.
Select Rows > Data Filter.
3.
In the Data Filter window, select city, State, and Region, and then click Add.
4.
Select Conditional from the Data Filter red triangle menu.
5.
Select MW in the Region list.
6.
Select OH from the State list.
Figure 8.11 Using the Conditional Option
The bracketed number in front of the column name indicates the order in which the column values were selected. In Figure 8.11, Region was selected first, so it has a [1] in front of the column name. State was selected second, so it has a [2] in front of the column name.
1.
Select Help > Sample Data Library and open Big Class.jmp.
2.
Select Rows > Data Filter.
3.
Select Grouped By AND from the Data Filter red triangle menu.
4.
5.
Click OR and add the sex column.
sex is added to the same group as age.
6.
Hold down the Ctrl key, select 14 from the age filter, and select M from the sex filter.
age and sex are in the same group. In the data table, rows that meet either the age OR sex conditions are selected. That is, all 14-year-olds and all males are selected in the data table.
7.
Click AND and add the weight column.
8.
Move the left weight slider to approximately 112.
Figure 8.12 Data Filter with Grouped by AND Condition

Help created on 10/11/2018