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’.
