Prediction matrix helps to build and test sophisticated predictions
Prediction itself is the process of calculating the likelihood of distribution over one or more variables whose values we are interested in, given the data we have about other variables. And the Prediction matrix assists with creating and testing predictions of how different events are expected to prompt a specific result.
It builds up a model of how a project functions. This model would then be used to create a predicted result, which would then be compared with a known (or planned) result.
In our example, this is reflected in the following: the higher the number in the cell, the more intense is its opacity, and therefore the probability for those values to which this cell corresponds in x and y axes will be the highest. But, bear in mind, that the explanations for x and y axes are already arbitrary, because it depends on the user.