Nice and short explanation. I liked the assigning of numerical values in the model.

Thanks for the video! Great explanation of the concept

This is madness! It is not possible to glibly multiply ordinals to get a meaningful answer. The scales represent probability distributions which can only me 'multiplied' by a Mellin transform. Cox in his paper on the risk in risk matrices covers this (search it up). Critical for this matrix to work are a few other considerations if a more useful qualitative scaling is used: 1. the qualitative scales need to be defined objectively, e.g. 'High Impact = 50% of the total NPV of the project.' or such like. 2. users of the technique need calibration training and their calibration based on historic examples 3. error bands must be considered. Note that even minor errors of judgement will move a risk between Low and High; this could easily result in a risk management disaster: over investment in risk treatment on the one hand, or completely missing a truly high risk on the other. Unless these potential weaknesses are dealt with, the matrix is worse then useless. Then a rigorous objective means of finding risks is necessary. This might include historic data, but if that's not available, a Risk Breakdown Structure needs to be developed from the project element structure and analyzed in terms of risk domains. The Soft System Methodology rubric of 'CATWOE' can be useful in this exercise. That said, I would also counsel against 'opportunities' being lumped in with 'risks'. The whole project is the 'opportunity', whereas risks represents contingencies that could de-rail the project and convert it into a waste of money. Options should be considered consistently through a project in terms of final out-turn value for the customer.

how does one identify Risk A, B, C and D to answer this question using this graph in the video on the PMP mock practice test

Thanks David for this video , These percentage values are decided randomly by Project manager or there is a mechanism for that as well ?