PROBABILITY

I started off my lecture in Data Analytics with the concept of probability at the Lagos Business School. Though this is not the first time I will be introduced to it, but this will be the first time I will make conscious effort to really learn the applicability of the concept of probability. Just before joining the programme, I had made up my mind that whatever I learn in class must have practical impact in my corporate and my personal life. Afterall, that was why I had invested resources in this programme. So, when the concept of probability was introduced by the facilitator, what was on my mind was how this will work in the real world.

There were so many concepts that need to be learnt before one can say that the concept of probability has been learnt. The first of them is the concept of experiment. Thankfully, I did sciences in school, so I know what an experiment is. This can either be a “scientific experiment or social experiment, what distinguish both are the subject of the experiment. This experiment which can also be called trial can be defined as any procedure that can be infinitely repeated and has a well-defined set of possible outcomes. An experiment can be random when it has more than one possible outcome and deterministic if it has one outcome.

The other concept worth of note in the study of probability is the sample space. This is a collection or the set of possible outcomes of a random experiment. A subset of sample space is usually referred to as an “event”.  Other concept of note includes uncertainty which is the reason for the concept of probability in the first place. Decision makers will want to know what are the chances that an action to be taken will lead to the desired outcomes. Or what is the likelihood of an action taken leading to the desired outcomes, or the odds that an action will result into an outcome that are favorable to the managers and indeed the entity for which they made the decision on.

Having learnt about the various concepts, probability can then be defined as a numerical measure of the likelihood that an event will occur. It is usually calculated as a ratio of an event over the sample space. The result of such ration is usually between zero and one. Where zero indicates that the event is quite unlikely to occur, while a value of one indicate that the event is certain to occur. So, which means that a Tuesday has a probability of one to be the next day after Monday. This is interesting! Values within zero and one are the various likely outcomes of the events. The close to certainty, the more the value gets closer to one, while the more uncertainty, the more the value tends towards zero.

Henceforth, when am giving my sales target result in the office, I must then remember to include in my presentation the probability of meeting my target. This seems very nice especially in analyzing how sure I am to cross the finish line before the year end. I know I am a high performer and I know that my aim is to make sure my probability tends towards one as much as possible.

##Annabel N

##EMBA 28