In 2011, the national average home price was $362,300. An average family consisted of 2.9 people with 1.9 children. If you didn’t catch a glimpse of this home and its fractional occupants, it’s because households like this only exist in the Land of Averages.
Averages aren’t always rational. What does a family of 2.9 look like? Do they live in a 1.23 storey home? Even if you consider your family to be “average,” chances are good that you can’t relate to those numbers.
Anyone who’s ever read an article on housing, the economy, healthcare, etc. has encountered averages. They’re easy to understand and to calculate, but they ignore how ambiguous a picture they paint.
Average home prices, for example, are easily dismissed in conversations. You may overhear someone say, “My friend Bob recently sold his home for $X and the family down the road from him bought their home for $Y – but I don’t know any homes around my area going for anywhere near the average price.”
What’s true about something as a whole does not necessarily apply to all of its parts. Average prices are useful for viewing trends over time but they don’t indicate actual home prices due to what can be a wide variation in prices among the homes included in the calculation of the average. A REALTOR® with knowledge of local conditions would be able to provide far more accurate information about home prices in Bob’s neighbourhood.
Averages are affected by what is included in their calculation. Consider the average height for a class of students. Add some really tall kids to the class and the average height rises. Excuse the tallest kids and the average height shrinks. In neither case did each student actually get taller or shorter despite a change in the average.
A multitude of general statistics – including averages – that are aggregated across different regions, industries, demographics (e.g. incomes) can mask underlying trends. The same is true for measures that make use of averages (e.g. average home price as a percentage of household income).
Using averages calculated for more detailed segments (e.g. geography, industry) or distributions (e.g. age, income) can yield insights beyond those available using simple overall averages.
The three tabs on the dashboard below illustrate examples of how averages can be misleading.
Although averages are not the best tools to rely upon for meaningful analysis, they’re sometimes the only ones available. Remember to take them with a grain of salt.