COVID and the Moving Average


Over the course of the epidemic we’ve been deluged by technical terms. One of these is the moving average, sometimes called the "running average" or "rolling average".

Although currently used to explain COVID statistics, the device is a powerful tool in many areas of our lives and businesses.  Let’s explore that a little.

As every math scholar knows, there are three types of “average”: the mean, the median and the mode.  For most of us, most of the time, we use “mean” and “average” interchangeably. “Mean” requires that you total up the measurements of all of the samples (weight, height, age, or whatever) and divide by the number of samples.

Thus, if you have five oranges weighing 4 ounces, 4 ounces, 5 ounces, 8 ounces, and 9 ounces, you would take the total of 30 and divide by five to say the average weight was 6 ounces. Interestingly enough, not one of the oranges weighs the “average” of 6 ounces, which shows us that the notion of “average” is not as precise as you might think.

Let’s say you’re running an orange packing plant. Buyers demand that the “average” weight of an orange be at least six ounces. And let’s also say that to date you've produced ten million oranges, nearly all of which were 8 and 9 ounce whoppers. By using the “all of the oranges for all times” method, you could now pump out some pretty scrawny little fruit and still be at the 6 ounce average.

But buyers are not fools. They’re not interested in last year, they’re interested in what they’re putting on the shelves today. They want to know what's currently coming out the door. This is where “running average” or “moving average” comes in.

In order to be more relevant, we might calculate the moving average of, say, the last five hundred oranges. This means that as each new orange tumbles onto the conveyor belt, we scratch Orange 501 off the calculation, and include the new one, constantly refreshing the calculation. In this way, we have a current and fresh value which is more meaningful than "the average since time began". By plotting moving averages on an "x,y" graph, we get a smoother curve which helps us understand trends.

Running averages have the benefit of keeping our eyes on the trends, not the aberrations. The spikes and the dips don't go away (and they have their own stories to tell), but they no longer distract us from seeing meaningful trends. If in our COVID world today we have a thousand new cases, but the running average is still four hundred per day and the trend is flat or down, we know we need to pay attention, but not panic. Conversely, if we have a day with zero new cases, but the moving average is still three hundred a day, we know we’re not yet out of the woods. Watching the moving average keeps us from getting distracted by blips.

Trend lines in life help us with big-picture thinking, of not getting alarmed about singular spikes or lulled by occasional dips. The trick, as St. Paul put it, is to “run with patience the race which is set before us.” By understanding and applying running averages, we are better able to be patient in our running of the race.



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