The politics of statistics

The politics of statistics.

Headline numbers can mislead voters.

The media is so very fond of headlines that grab attention but do not provide very accurate information. Unless you can find the definitions used and the basis for the figures publicised, you can not have any validation of the truth of what is being proclaimed. Finding the definitions and actual numbers used, is not easy. Just as in those advertisements for cosmetics, which are fond of saying X% of women think this product will improve their appearance, while the tiny print at the bottom of the screen says something like 20 out of 75 people surveyed. Even this does not tell the real truth, what age were these 75 people? what was their appearance like to start with? did they undergo controlled tests with scientific measurement of the results? or did they just agree with some one saying they look better? 75 out of a world wide potential number of customers, several billion, is not statistically relevant at all.

In the recent election, in Britain, the socialists trotted out the slogan that 14 million British people are in poverty. The media especially the left leaning “liberal” media kept repeating this as some sort of irrefutable truth. The voters did not seem impressed, as the Conservative party won a large majority and formed a government, but this claim of 14 million in poverty in Britain, was misleading and could have led to an election win that was based on deceit; the voters now seem, in general, to be well aware that political statistics are not often actually what they seem. The attempted deception was arrived at by using a “definition” of poverty, that was very different from the average persons. The left media and politicians, then made sure their own definition of poverty was not published openly. They claimed that poverty is having wealth or income, that is a low proportion of the average. They decide what proportion and keep this out of public scrutiny. This is a political trick that enables them to claim just about any number of people are in poverty. Set the proportion at 49% and half the population is in poverty simply because they have less than the other half. They may all have homes, cars, smart TV and incomes of £30,000 a year, but under this political definition they could be “in poverty.”

Statistics are only of value if you know how they were arrived at. We all see environmental statistics shouting that the climate is heating up and we see counter claims that it is steady. All of the figures need to be scrutinised with caution. Those who wish to see “evidence” supporting their own political agenda will select the data which does just that. The planet earth is very old. Humans have only existed for a relative short part of this time. Humans who kept verifiable written records, have only existed for a very short period of history. Humans who have had the technology to make world wide, accurate, data gathering records, have only been around for the last 35 years or so. Scientists have, unfortunately, become dependant on funding; the sheer complexity of technology required, means they need a huge amount of money if they are to continue to work. This funding is not given out just because the scientist wishes to gain knowledge. Funding is dependant on “cost to benefit analysis” and the definition of benefit is set by the people with the money. If the scientist does not agree to supply the “benefit” the funder wants, then no funding is supplied. The temptation to “extrapolate” or “simplify” data, to provide enough “benefit” to ensures future funding, is too strong for most. Humans have an extraordinary ability to become convinced they are right, when little or no evidence is available, and scientists are humans.

Political statistical trickery is probably common in all nations, even one party states seek to “prove” to the people they are doing the right things and so statistics are publishes showing this or that advance. Any study of Soviet Russian history, especially the Stalin eras, shows that political statistics and truth seem a long way apart. In democracies the origin of head line figures is not always obvious. Take a close look at a web headline 4 December 2020. It said 3.5 Million people in Britain have never had a job. Consider this for a moment; Britain has a population of very approximately 65 million. So 3.5 million is about 5% of the population. The head line may be accurate but it could also be misleading. How many people in Britain work in the “black economy” and never pay tax. How many people in Britain are and always have been, full time careers? These are people working hard and long, to care for relatives, they do not have the time for paid employment but they work harder than most. How was this figure of 3.5 million arrived at? Does this include those unfortunate enough to be born with disabilities that prevent work? How accurate is it? How many illegal immigrants declare they are earning? How many drug dealers pay tax?

Figures, without supporting data, are worthless. Data that is not verifiable is worthless, yet governments are elected and governments base long term policy, on such suspect statistics. We all suffer the consequences of wrong decisions. We should all demand more than just headline numbers.