Thinking about distributions and odds and their limited value in living and dealing with uncertainty and risk some more.
I am not anti-statistics. In many aspects of my work I make use of various stochastic techniques. Used properly in analysis these techniques can be very helpful in discerning patterns and provide opportunities to sense the implications of scenario choices such as modelling.
What I am suggesting is that in our day to day lives where we actually live with uncertainty and risk (U&r) we rarely consider distributions at all. Why? Because we often don’t really know them. When we do have a sense of them they don’t provide any real help in any specific decision situation. Why? Because they are plots of possible outcomes, not what the next outcome will be. Example, toss a coin, the distribution will be that over time we would expect to see heads and tails to show about half the times the coin is tossed. Yet, if we are going to toss the coin one more time, and your decision is to go west on heads or east on tails, which way are you going to go? It is not half west and half east! It will be one way or the other. Knowing the distribution over time is not in the least bit helpful for the next toss.
One significant reason of course is the coin tosses are truly random. The past is no predictor or has any causal influence over the next toss. Of course there are many situations where the past does influence the future. Over time we develop habits, and habits (when we know them) can be used to predict behaviours by people and animals when facing future situations that are generally covered by these habits. People who are not really aware of their habits in sorts of situations may act more consistently because habits are often non or minimal thinking responses. People who are aware of their habits may be more discerning about whether a specific situation is use different enough to warrant a non habitual alternative action.
In another sense, having a sense of distribution may lead to inappropriate judgements. Let’s say we know that at any one time 30% of females within typical child bearing age span are pregnant. This suggests that at the same time 70% are not. We can plot this information. So does the plot suggest that at any one time a child bearing aged female is 30% pregnant? Of course not! This mean/weighted average value does not apply to any one/single individual in the applicable population. She is either pregnant or not pregnant, the statistical mean calculation is not useful. would any of the typical statistical calculations be useful here? NO! Because, the way we interact with world is in specific moments and choices. Statistics is more often about understanding the behaviour and attributes of populations.
So unless we have a vocation that is focusing on population level attributes and behaviours, statistics will always have a modest use in our lives.
Yet there are some situations where understanding population attributes is useful for action. Take the famous sales funnel example: It takes (on average) 100 cold calls to get 10 opportunities to make a sales pitch; it takes 10 (on average) sales pitches to make one sale. The value here? We appreciate the typical amount of effort it will take to make a sale. As the effort is behavioural in nature, we can set performance goals around making the efforts to obtain sales.
So let’s get back to risky like situations. How can we use statistics to help inform us regarding our choices? The sales funnel example can work here too. Actions can move us from the “mystical” mean towards one side of the distribution or the other. a good example is safety. Engaging in unsafe behaviours will proportionally expose us more to experiencing near misses. Being exposed to near misses exposes us more to having a safety incident/accident. Will someone who never engages in unsafe behaviour never have a safety accident? No, of course not. Shit can happen, especially if other causal factors come into play (e.g., sudden equipment failure).
What is interesting is that the sales funnel and safety situations are not truly random ones at all. Our behaviour can influence whether the next choice or act will expose us to success or mishap. I am not sure, but I suspect that many risk and uncertain like consequences that we experience have known knowable cause and effect circumstances to them.
This means, without paying attention to any notions of calculated distribution or odds we can influence our “likelihood” of being “more” at risk and/or exposed to specific kinds of uncertainty. The first time anyone tried riding a bicycle, that person was totally exposed to the uncertainties of riding such a vehicle. Not risk but uncertainty, because the pitfalls were unknown in any sense, and even those mishaps that could have been foreseen would have had lots of question marks about them. After the first time though, subsequent rides and riders got more and more information such that main uncertainties became risk like. Where uncertainties remain for even the experienced cautious bicycle rider is when the engage in riding in an unfamiliar area or with an unfamiliar and non checked over vehicle.
So in conclusion: looking at statistics to help us manage risks and uncertainties in our lives is for many of us in our day to day activities minimally helpful. We need to look elsewhere for the tools and techniques to help us navigate these shoals. Shoals is actually a pretty good metaphor for how we can best successfully live within a universe of U&r like circumstances.
Again, because the use of statistical based notions of risk are virtually meaningless to us in real life we are then mainly facing a life filled with uncertainties: that which we know nothing about, or somethings about but not enough to make them rule risk like.