Groceries and Football
I confess that the idea for this article is not entirely my own. The statistics professor my sophomore year is to blame. He introduced me to Darrell Huff’s 1954 book titled “How to Lie With Statistics”. I haven’t been the same since. I question everything. My second confession-I started writing this as I was watching Ohio State win a National Championship.
Of late, it has been hard to ignore all of the statistics that surround college football. The early rankings were based on, more or less, past performance and strength of schedule. For example, the SEC had been a football powerhouse heading in to the 2014 football season. This was proven by the SEC’s success in bowl games where they faced opponents from other conferences as the 2013 came to a close. Therefore, teams like Alabama were ranked high, along with teams like Ole Miss and Mississippi State. As the season wore on, these teams performed well against their out of conference “pancake” competition, and performed well in their own conference. As the season ended, not well for many, it became clear that these teams were overrated. The teams, and conferences strength in 2013 did not necessarily carry into the following season.
Take a simple statistic such as, “team X has only allowed 4 sacks all year”. Is this good, bad, or indifferent? It would be helpful to know who this team played, and how their opponent’s defenses are ranked (as well as how many games they had played before this stat was tabulated). Allowing 4 sacks to inferior opponents is not necessarily a great measurement of an offensive line’s ability to protect the quarterback. Football is fraught with misleading statistics. But misleading statistics are everywhere.
“My son averages 95% on the exams he takes”. What if every other student gets a perfect score, every time?
A client recently showed me a drawing that her son did for a High School art class. I was amazed, it was absolutely incredible. She said, “He’s only average in his class”. I said, “Well, then, his entire class must be above average”.
When I’m meeting with my clients, it’s impossible to avoid numbers and percentages. One client may spend $8,000/month to cover their expenses. Another may spend $20,000/month to cover their expenses. These numbers are useless without a valid and relevant frame of reference. If the client that spends $8,000/month had a pre-retirement income of $7,000/month, the $8,000/month is really high. If the client that spends $20,000/month had pre-retirement income of $30,000/month, the $20,000/month is very low.
I was recently sharing my idea for this article with my wife (who happens to be a serial ESPN Radio listener). So I made up an example and said, “I have a single female client that spends 15% of her income on groceries”. She said, “Wow, she spends a lot”. That’s a normal reaction. But then I said, “She makes only $25,000 a year.” Clearly, someone with a lower income spends a higher percentage of their income on “staple” items like food and utilities.
For better or for worse, statistics that are based on past performance are used to evaluate and compare investment alternatives. One important stat is something called “percentile rank in category”. Think of this as a student’s ranking in a class of peers. A percentile ranking of “1” indicates that the subject investment has had a rate of return that is better than 99% of its peers. For example, Fund A has a percentile ranking of “1” because it has a 10-year annualized return of 8%. Fund B, on the other hand, has a 10-year annualized return of 5%, and its percentile ranking is “60”. Fund B underperformed more than half of its peers.
But what if Fund B had a 10-year annualized return of 7.5%? One would expect it’s ranking to be very high, right? If Fund A is in the top 1% based on a return of 8%, and Fund B has a return that is just one-half of one percent less, surely it would have to ranked very high. Not so. Fund B could have a percentile ranking of, well, even 50. How? If most of the investments in this category had a very narrow dispersion of returns, more than 50% of which were in the 7.5%-8% range.
It has been reported recently that the cost of healthcare is going down. This is not the case. Healthcare costs are not falling, they are simply increasing at a slower rate.
So the next time you hear or read a statistic, take it with a grain of salt. It’s all relative. And maybe the source had an agenda and simply used the statistics in favor of making their point.