Hey Everyone,
The issue with hard data and research is that many times people tend to place more or less weight on specific facts, depending on whether or not that information happens to strengthen their case.
This is known as confirmation bias, and the fictional character Sherlock Holmes summed it up quite nicely in the following quote.
"It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts."
For example, it's far too easy for economists who've been banging the hyperinflation drum to dismiss yesterday's U.S. inflation data as if it's some sort of anomaly, when actually the figures were blissfully normal.
When objectively analyzing data, it is usually the outliers, the extremes, that should be more heavily scrutinized.
Conversely, when a number comes in that is quite average given historic norms, we should be less quick to try and discount it.
Of course, we never want to fall into the trap of placing too much weight on a single data point, so here we can see the Consumer Price Index over the last few years. Feel free to draw your own conclusions.
