There is a story of a man who wanted to cross a river that had a depth of “four feet on average.” Feeling fairly confident about it he set about on his journey only to drown somewhere near the centre.
Beware of the ‘averages’!
In his brilliant little book- “How to Lie with Statistics”, Darell Huff introduces us to this particular concept and how the human mind gets lulled in to understanding the term ‘average’.
Think about it like this. Suppose you were building data on incomes of all your neighbours. If we took an average then it is possible that with some accuracy we could tell you what each person was earning. But what if one of your neighbours was Mukesh Ambani? Wouldn’t the average income number be way off the mark?
Finding exceptions in your Data Set
A sense of confirmation bias (covered earlier) and an inability to conceptualize a black swan (like having Mukesh Ambani as your neighbour) can create problems for us like the man who drowned. It is therefore imperative for us to:
1. Understand the sample set of data that we are reading and
2. Actively look for exceptions to the rule.
How does this play out in your finances?
“Equity markets have returned 15% on average over the long-term.”
“Real-estate will beat inflation on average.”
“My salary will increase at 10% per year since that has been the past average.”
Can you see exceptions to all those cases? What can cause them? Are you at the crest or trough of your sample space? Each of these can have wide-leading ramifications to the way you ‘plan’.