A Sum-by-Category statistic totals all statistics which belong to their category. This is useful for totaling all like statistics without the need of creating an equation which can change often. Consider a sales department with ten employees where there's some turnover. You can create an equation which would add each saleperson's stat is listed in the equation but you would need to change the equation each time you added or removed a sales person.
Sum-by-Category stats are simple and easy to set up.
The first step is to make the statistics you want to total part of a category. In our example we are going to create a Total Sales stat so we are going to make Sales US and Sales Europe part of the Sales category as shown in and below.
Do this for all statistcs you want totaled together.
In the first page of the Statistics Wizard enter the name and abbreviation, then select the Sum by Category option for the Stat/Graph Type as shown by .
Do not enter the same category in the Category field as this would cause the stat to be added to itself, which is not allowed. A Sum-by-Category can, however, be part of another category allowing you to create tiers of totaling statistics.
Set the options you want on the second page of the wizard. Click Next.
When the Sum by Category option is selected, a third page becomes active.
In our example we've made Sales US and Sales Europe part of the Sales category, select the Sales category from the dropdown list as shown by .
The statistics which are part of the selected category are listed as shown in .
From this point forward when a value is entered for Sales US or Sales Europe the value for Total Sales will be recalculated automatically.
NOTE: Unlike Equation statistics, Sum-by-Category stats will compute a result even when some values have not been entered and it assumes missing entries are zero until an actual number has been entered.
When viewing a graph of a Sum-by-Category stat the hovering notes are different and show the how the total value was arrived at. See the screen shot below.