I find that I learn best when I can draw everyday analogies of a concept being taught. As a result, when I try to explain things to people, I tend to draw examples from common, everyday things and activities to drive the point home.
Once of such concepts that we learnt in Data Analytics is Probability. Probability is really at its core, the likelihood of a chance of occurrence. Given a specific context, probability seeks to estimate the chances of a particular outcome or range of outcomes. Of course, as with many things mathematical, beyond this seemingly simple concept, layers of complexity and complications begin to build. It was therefore no surprise that a key question that dominated many others in our Data Analytics classes was, “how does one derive the data to start with?”
I have two analogies that I try to explain this question with. The first is assume you see a professional waiter carrying a roof-high stack of ceramics plates and coming down a flight of stairs, “what would be your reaction?” You will probably not think much of it. Now imagine a ten-year old carrying a stack of ten ceramics plates, “how would you react?” The more likely reaction is that you advise the ten-year old to carry the plates in smaller. The question though is why? Why does it not bother you when a professional waiter is taking a similar risk? The answer of course is that you have quickly estimated in your mind that being a professional, the probabilities of a mishap that causes the plates to break is significantly lower. You have estimated the chances, the probability of an outcome (a mishap causing the plates to break).
I also like to use the analogy of travel route. Many of us have various routes leading to our offices from home or any route we frequent. On any given day however, we decide what route to use, even without or sometimes even going against recommendation by map applications, based on estimation of the level of traffic on the various routes. At that instant, we are estimating the probability of traffic on each route based on the analysis of our experience travelling the various routes over time.
The fact is that many people employ probability almost on a daily basis. However, this is typically expressed as qualitative information like ‘high, moderate, low’, ‘successful, unsuccessful, neutral’ or ‘most likely, probably, least likely’. But these expressions may mean different things to different people and even to the same person, given different contexts, may mean different things to the same individual. Introducing data and attaching numbers to the potential occurrences however introduces the complication with probability. But as Andy Dunn, American entrepreneur and co-founder of Bonobos Inc. put it, “passion provides purpose, but data drives decisions.”
Data is hence pertinent to eliminate ambiguity, ensure a shared understanding and consistency of meaning. As Jim Barksdale, American executive and former president and CEO of Netscape quipped, “if we have data, let’s look at data. If all we have are opinions, let’s go with mine.” Without data, it is anybody’s guess.
Analysis of financial statements