In the past few days, several people have posted statistics on Facebook that caught my attention. Actually, people are always posting statistics. Most of the time I can laugh them off. But the last two were the last straw.
First, let me assure you that I aced both undergraduate and graduate level statistics courses despite being a girl, or perhaps, because I’m a female. I got pissed at the idea that I would have trouble with the subject just because I was female so I didn’t, but this is somewhat beside the point.
In this paper I will try to explain about numbers and why they may not make sense. The first statistic that drives me crazy is the one on longevity. People who study such things like to note that those who are in their nineties now lived on an average 4.7 years longer than their parents. Okay, this is valid. It is simply a measurement of what happened-not a problem. Because it is history, it accounts for all the variables of diet, environment, health care and income.
What makes me pull my hair is when the number 4.7 is then used to predict that my generation will live 4.7 years longer than our parents because of improvements in health care or whatever. You cannot take a number from the past and apply it to the future without accounting for all the differences between the two generations.
Those in their 90’s now were born during a time when women were discouraged from drinking while pregnant. They were not prenatally exposed to DDT, or to radiation beyond the normal base level of their time. As children, our parents or grandparents ate non-processed food. They walked to school. (Through ten feet of snow—uphill both ways.) They were not exposed to High Fructose Corn Sweetener in all their food. As young adults they were not exposed to Agent Orange and more radiation. They were not exposed to GMO’s and the pesticides clinging to them until they were in their late 70’s.
Younger generations have a hugely different toxic exposure over their entire life than the greatest generation experienced. We don’t know the long term effects of the chemical soup we live in, and we won’t know what those effects are until my generation passes. The predictions for how long we will live are about worthless.
The second stat that made me ponder was something published in the Washington Post that said only 62% of our workforce is employed and that many of those unemployed are not seeking employment. The person who related the information to me interpreted this as a terrible thing. Huh?
The number was presented on Facebook without context and again without consideration for the variables. If you stop and consider the variables the number isn’t so bad. Of course we don’t know their definition of available work force. Let’s assume it includes all adults between the ages of 18 and 65. Of the 38% unemployed we need to subtract those in college or being retrained for a career change and those who decided to retire as early as age 55. That whittles the number down some. Now we can also subtract those who are unemployed due to health or injury and will eventually return to work or receive benefits. Next, let’s subtract those people who have no intention of seeking employment because they choose to stay home with their children or an ailing parent. We also have a few people who are unemployed with no intention of working because they have enough wealth to support themselves for the rest of their lives. The 38% unemployed doesn’t sound so alarming when you consider the circumstances of that 38%. The image presented to me was of people living in squalor and surviving on the public dole as compared to people playing golf, or driving kids to soccer or taking a frail parent to physical therapy.
The employment number irritates me because it was given without context and appears to be a non-issue blown up as a problem. It detracts from some real issues in our employment sector. How many employed people get paid for every minute they work? How many people are part-time or working temp jobs? How many people work full time but low wages force them to choose between buying food or paying for a place to live?
Next time you see a statistic stop and look at it. What is the context? Does it consider all the variables? Does it really represent reality? Does it say what the presenter thinks it says? Ask where does this number come from? My example of the 38% unemployed that included those who are not seeking work is based on an innocent enough number. It appears to be valid, but the interpretation left out too many variables. So, the number may be okay, but be wary of the person interpreting it.