April 16, 2019

Last week, I introduced “How to Lie with Statistics” (a 1954 book) as a guide for reading the daily news. The bad news bears always seem to want to make our troubles worse than they already are, so they use the power of numbers and charts to make our economic situation seem hopeless, or dangerous, or both.

Five Examples of How to Spot the Misuse of Statistics

There are so many tricks of the trade that I can hardly scratch the surface, but here are five for starters:

#1: Partisans choose time frames to suit their bias. If I want to prove that Gold beats Stocks, I start the chart in 2000, when gold was $250, and NASDAQ was 5,000. If I want to prove the opposite, I start the chart at gold’s peak of $850 in 1980, when the Dow was also about 850. People selling gold (or stocks) will pick the starting date to fit their bias. I can reduce this time-choice bias to a four-line doggerel:

Let me choose the Date to Start,
And then the Date to End,
And I can draw a Fancy Chart
That Proves My Favorite Trend

This is true of social statistics, too. Violent crime is way down since 1991, but it is up the last three years, so people who want to scare you say, “Crime is up,” but the “alternative” (truer) fact is: Crime is down.

Graphs are for illustrative and discussion purposes only. Please read important disclosures at the end of this commentary.

#2: Beware the difference between median and mean: The word “average” can be misleading. Is it the median (mid-point of all cases) or the mean (all cases added together, divided by the number of cases)?  A Texas article once claimed that the “average income of Texas business school graduates exceeds that of Harvard Business School graduates,” but the average (mean) was skewed by a few oil-field billionaires.

In the chart below, there is a huge difference between the “median household income” (orange line) and “mean household income” (red line), based on the SAME Census data, because multi-millionaires push the “mean” well above the “median,” but there is another big question posed by the three BEA statistics!

Graphs are for illustrative and discussion purposes only. Please read important disclosures at the end of this commentary.

The key to this wide array of lines is in the definition of “household income,” which leads us to point #3:

#3: Beware shifting definitions or implied (but false) definitions. The Census Data (the two lowest lines above) include cash income only, based on Census data. They do not include extra benefits and in-kind income. Pessimists who wish to say incomes have stagnated use the Census data for median income, which is up 2% from 2000 to 2017, but more comprehensive income data from the Bureau of Economic Analysis (BEA) shows that personal consumption per household rose 28% from 2000 through 2018.

#4: Falsified pictures inflate statistics in your mind. Very often, charts contain pictures which mislead the reader as to the intent of the numbers displayed on the chart. For instance, statistics about the number of “children who go to bed hungry” are based on surveys of parents who are asked if they were ever unsure at any point in the last year where the next meal would come from. That does not equate to actual hunger. Global warming advocates picture worst-case outcomes of rapidly rising ocean levels and let you assume that worst case is what “99% of climate scientists” believe. Whenever there is an appeal for funds, dramatic pictures are based on worst-case scenarios while the statistics are dominated by milder cases.

Here’s a picture showing how carpenters in America once earned twice what carpenters in Europe earned:

Graphs are for illustrative and discussion purposes only. Please read important disclosures at the end of this commentary.

The artist drew a bag of money twice as high, but a bag of money is three-dimensional. A real bag of money that is twice as high would also be twice as wide and deep, representing eight times as much cash.

#5: Small numbers can seem huge using percentage increases. When I had knee replacement surgery in February, my physician said I had a five times greater risk of infection due to a skin condition. I asked what the real odds were. He said the normal risk was 0.1%, but my risk was 0.5%, so I green-lighted the operation. “Five times greater risk” sounds terrible, but one chance in 200 was a risk I was willing to take, considering that infections can also be treated. Here are some similarly scary headlines, decoded:

“85,000 times as much rain fell in Palo Alto one morning as fell in the same period in the last 36 Julys” (0.19 inches in six hours compared to 0.01 total in 36 previous Julys: Do the math. It works: 85,000x.)

“Over 14% of Radar Mechanics went crazy last month due to overwork,” so the Pentagon rushed in 35 new radar mechanics, even though the headline was based on just one mechanic out of seven (14.3%).

Overall, just realize that partisans are willing to mislead you with numbers that seem accurate but aren’t.

About The Author

Gary Alexander

Gary Alexander has been Senior Writer at Navellier since 2009.  He edits Navellier’s weekly Marketmail and writes a weekly Growth Mail column, in which he uses market history to support the case for growth stocks.  For the previous 20 years before joining Navellier, he was Senior Executive Editor at InvestorPlace Media (formerly Phillips Publishing), where he worked with several leading investment analysts, including Louis Navellier (since 1997), helping launch Louis Navellier’s Blue Chip Growth and Global Growth newsletters.

Prior to that, Gary edited Wealth Magazine and Gold Newsletter and wrote various investment research reports for Jefferson Financial in New Orleans in the 1980s.  He began his financial newsletter career with KCI Communications in 1980, where he served as consulting editor for Personal Finance newsletter while serving as general manager of KCI’s Alexandria House book division.  Before that, he covered the economics beat for news magazines. *All content of “Growth Mail” represents the opinion of Gary Alexander*


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