The Tiger That Isn't

Title: The Tiger That Isn’t
Authors: Michael Blastland and Andrew Dilnot
Publisher: Profile Books 2008
ISBN: 978-1-86197-839-4
Pages: 174

An interesting book on the facts (or absence of it) behind numbers we encounter in everyday life. We are usually taken aback by the overstated claims of vested interests who represent the figures making them appear to be extremely huge and alarming. This book goes behind the numbers and expose them for what they are worth. Blastland is a writer and broadcaster while Dilnot presents the series More or Less on BBC Radio 4. Even though both of them are not decorated with very high academic distinctions, the subject matter turns out to be extremely lucid and enjoyable. This work may also be called a page-turner, because the number of pages is quite small. In fact, one can finish, or tempt to finish it in one go.

Eleven major aspects of numbers presented before the public are analysed in detail. They are, size, counting, chance, averages, targets, risk, measurement, data, shock figures, comparison and causation. When we see large numbers as the size of some quantity, we should ask whether the number is really big. Several examples are given, one of which is the number 3.12 billion. Even though it may look huge, it turns out to be (in the case of amounts of money) one unit each for every British citizen for every week of the year! So, if the government spends such a sum, it can quite rightly be called paltry. In the case of counting, it may not be straightforward, as the definition of a parameter can be vague in everyday life and the sampler may find hard pressed to assign it to a particular group. We should follow the guidance of Aristotle in such matters, which says, “It is the mark of an educated man to look for precision in each class of things just so far as the nature of the subject admits”. Another numeral which frightens us most is chance. When the media report clustered cases of cancer near to mobile phone towers, we should not fall in the trap at once, but understand the nature of chance. In fact, it is not at all surprising to detect several cases in a neighbourhood, without any extraneous reason at all. Also, one case is analyzed to fine detail. When speed cameras were installed on highways, the accident rates came down. The authors argue that the fall may be due to a statistical fact called regression to the mean which means that the number of a particular incident falls after a peak. Normally, speed cameras are installed in those stretches of the road where there was a severe spike in the number of accidents.

Averages can be deceiving. For example, if we consider 100 people, one of them being single-legged, we can see that 99% of the people are above average when compared on the average legs per person. This is particularly faulty in the case of incomes, where most of the people will be above average. Median, the value which separates the upper 50% from the lower half is a more realistic parameter. Another witty example is the case of a drunkard zigzagging on the road. If we take his average position over a period of time, it will be on the centre of the road, he being safe there. But in actual life, he is most likely to be run over by a vehicle.

Risk parameter is one quantity which is almost always blown out of proportions. A good discussion on whether there is any finding by a research team on the effects of mobile phone radiation is given, as “In January 2005 the president of te British Radiological Protection Board announced that risks revealed in new medical research into mobile phones meant children should avoid them. The resulting headlines were shrill and predictable. He issued his advice in the light of a paper from the Karolinska Institute in Sweden that suggested long-term use of mobiles was associated with a higher risk of a brain tumour known as an acoustic neuroma. The news reports said that mobile phones caused it to double. With mobile phones you could begin with the reassurance that these tumours are not cancerous. They grow, but only sometimes, and often slowly or not at all after reaching a certain size. But how big was the risk? When we spoke to Maria Feychting of the Karolinska Institute, one of the original researchers, a couple of days after the story broke, she told us that the baseline risk was 0.001 per 100,000. This is how many would ordinarily have an acoustic neuroma if they didn’t use a mobile phone. With ten years regular phone use, the much-reported doubling took this to 0.002, or 2 people in 100,000. Would Maria Feychting stop her own children using mobile phones? Not at all: she would rather know where they were and be able to call them. She warned that the results were provisional, the study small, and quite different results might emerge once they looked at a larger sample. In fact, it was usually the case, she said, the apparent risks like this seemed to diminish with more evidence and bigger surveys. Two years later the worldwide research group looking into the health effects of mobile phones – Interphone – of which the Karolinska Institute was a part, did indeed produce another report drawing on new results from a much larger sample. It now said there was no evidence of increased risk of acoustic neuroma from mobile phones, the evidence in the earlier study having been a statistical fluke, the product of chance, which in the larger study disappeared.

When taking samples to base judgements on, it should be unbiased and data collected should be clean. Another aspect of media scare reporting is giving shock figures, which might not be pointing to the truth. Natural variations in the sampled data are not usually taken into account. An example is the doping test for sportsmen. The tests are to find out the level of testosterone in blood, as “The hormone testosterone occurs naturally and is typically found in the urine in the ratio of one part testosterone to one part epitestosterone, another hormone. The World Anti Doping Agency says there are grounds for suspicion that people have taken extra testosterone in anyone found with a ratio of 4 parts testosterone to 1 part epitestosterone. The threshold used to be 6:1, but this was considered too lax. However, there were documented cases where this level was up to 11:1. Also there are whole populations, notably in Asia, with a natural T/E ratio below 1:1, who can take illegal testosterone with less danger of breaching the 4:1 limit. In short, there is abundant variation”.

 

Causation and correlation are two factors which need to be studied in detail to obtain the linking criterion. The postulate that overweight people live longer than thin people is true, but the reason is not their overweight. Rather, the cause might be that the thin people be affected with more diseases.

A good work and recommended.

Rating: 3 Star