As mentioned above, the idea is to consider not only implications but also association rules. While each implication rule follows a path that leads up in the diagram, an association rule follows a path that leads down. In Figure 1 these confidence levels are indicated in the shaded boxes which are attached to lines in the diagram. Each line represents a simple association rule. It should be noted that these are only the simplest possible rules.
Association rules can be more complicated and involve several concepts and longer paths.
Coming back to the question of whether male students would receive C's if there were more male students, the levels of confidence and support should be considered. The percentage of students to which a concept refers is considered the support for that concept. Both could be considered too low to draw any conclusions. These types of considerations are common in statistical analysis where it is important that populations are large enough to be significant. The advantage of FCA is that a user can explore the data interactively by changing levels of support and confidence and then studying the resulting graphical representations.