Fibbing stats
There’s a contemporary fascination with numbers that at times threatens to become credulous. There are many things we as a society can measure and put in the numerical form of data where the numbers tell us useful things about the world. On a large scale, we can measure government spending and debt, for instance, as well as employment, the crime rate, and national growth. And while numbers can seem more scientific than individual stories, they can also prove too abstract, misleading, or even simply wrong. And since we’re ultimately dealing with people, the numbers can always be used with the intention to confuse and mislead, to give one person or group an advantage over another.
As it happens, people write books about such things, and unfortunately, I haven’t gotten around to reading them. In fact, I haven’t read too many at all that were strictly about using such numbers, properly or not. Fortunately, though, others have seen fit to write book reviews about books on statistics, one of which I came across at the online journal Quillette.
The book in question is Bad Data (2022), written by Georgina Sturge, who works in the library of the U.K. Parliament. From the review:
This informative, reasoned, and apolitical book offers a string of examples to show that statistics are not always what they seem. Some statistics are rigged for political reasons. Others are inherently flawed. Some are close to guesswork. Even crucial variables such as Gross National Income and life expectancy are shrouded in more uncertainty than you might think. We don’t really know how many people live in Britain legally, let alone illegally. The number of people who are living in poverty varies enormously depending on how you measure it.
Politicians, of course, are in a line of work that involves selling things, and numbers are often bent and adjusted by those who sell things, usually by overstating the importance of favorable statistics while downplaying or omitting unfavorable numbers. As John Maynard Keynes supposedly said: “Politicians use statistics like a drunk uses a lamp post: for support rather than illumination.”
The book offers some general guidance for statistical skepticism in the general public:
If you take one point away from Bad Data it should be that the vast majority of statistics are estimates, some of them are very rough estimates, and statisticians are constrained by limited resources and bounded knowledge. It is not a crisis. Outright fraud is rare, but when confronted with an impressive statistic, especially when it seems surprising, it is worth asking, “How do they know this?” Very often the answer will be that they don’t really know it at all.
Nevertheless, nearly all of politics, public policy, and governance relies on statistics and data, and from where the voting citizen lives, the numbers have to be presumed to be honest, true, and accurate. Otherwise, the output of the entire process has to be off—perhaps by a wide margin.
At any rate, all this leads me back to the same conclusion—and definitely my bias: Good, efficient government from a central authority is essentially impossible, even if it were safe to assume government were run only by individuals who are not corrupted by ambitions of power or wealth. Now if only I could figure out how to read more books.
🤔🤔🤔
On the subject of stats, I posted this at TMD:
"China’s National Bureau of Statistics reported this morning the country’s gross domestic product grew just 3 percent in 2022, down from its 8.1 percent rate of GDP growth in 2021. The data, if accurate, would make 2022 China’s second-weakest year of economic growth since 1976, behind only 2020."
OR, China’s National Bureau of Statistics reported this morning THAT IN SPITE OF THE PANDEMIC, the country’s gross domestic product grew 3 percent in 2022, down from its 8.1 percent rate of GDP growth in 2021. The data, if accurate, would make 2022 China’s second-weakest year of economic growth since 1976, behind only 2020, the start of the pandemic. In context, that is an accomplishment.
Statistics are about what we do with them and what context we offer or leave out.
So, for some odd reason, when I flushed the toilet this morning I started thinking about water and how we have it in such abundance. Without thinking about it, and while others die of thirst, we wash our cars and pets, we water our lawns and fill swimming pools, we wash our driveways (neighbor does it regularly) and run sprinklers for our kids to cool off, we fill fish tanks for our amusement and we have water parks ------- all with drinking water and without a thought. That led me to think, for a moment, about how we live in a world of such abundance. There are so many variations of orange juice that I find it annoying. How many trees are cut down for toilet paper? Twice as many for 2-ply? I could go on but that toilet flush got me thinking. Just read the stats in the center drawing. https://rehydrate.org/water/ (Anne, this is not music.)