I have met many THEY SAYers from different walks of life - relatives, friends, social acquaintances, business associates, broadcasters, newspapers - in fact a THEY SAYer can be any conveyor of knowledge. Here are some examples from the THEY SAYers' knowledge base:
* THEY SAY the winters will get colder and the summers will get hotter.
* THEY SAY tsunamis and earthquakes will become more frequent.
* THEY SAY eating carrots helps you see in the dark.
* THEY SAY you should eat five vegetables a day to keep fit and healthy.
* THEY SAY alternative treatments such as special diets, herbal potions and faith healing can cure apparently terminal illness.
* THEY SAY (or rather SAID thirty years ago) North Sea oil would run out within thirty years........and it didn't!
The examples are endless and the last example of thirty years ago is when I started following and getting thoroughly pxxxxd off with THEY SAYers! The punch lines are usually employed to support an argument, so a mother trying to encourage her child to eat his carrots might quote the benefit of being able to see in the dark. As the child gets older and plucks up courage to challenge his mother, perhaps by asking "Who are THEY?", a typical response is "It's a well known fact!".
Well who the fxxk are THEY? A very good question! Newspapers can be a source of THEY particularly the 'popular press' that creates news rather than just reporting it. TV all-day news programmes often flash up one-liners between programmes to whet the appetite with headlines such as "Researchers believe that drinking alcohol in moderation can reduce the risk of heart disease" or conversely, "Studies show a strong link between alcohol consumption and cancer".
As I grow older, I like to think I am getting wiser. In my view wisdom includes looking at things objectively. Purists would say that's impossible because any opinion, by definition, is subjective. OK, we'll my response to the purist is that we should form opinions on as much evidence as possible, rather like a court of law does before arriving at a verdict. So when a THEY SAYer fires a shot across your bow, the counter attack could be "Where's the evidence?". If the evidence is "I read it in the newspaper" or "I saw it on TV", well sorry but that's not good enough. Francis Bacon said "It is the peculiar and perpetual error of the human understanding to be more moved and excited by affirmatives than negatives." In other words, we believe what we want to believe and we have a tendency to find evidence that supports our pet theories. So if the THEY SAYers' 'evidence' cannot be supported by well documented and validated research programmes then it should be dismissed out of court! Maybe the mother's statement to the child who won't eat his carrots should be "There are those who believe eating carrots can improve night vision but I know of no reputable evidence to support this theory". The trouble is that such a statement is unlikely to affect the child's dislike of the taste of carrots, so if mum doesn't want the child to grow up into a faddy eater, maybe a better tactic is "Take it or leave it, there's nothing else on offer!".
Well as I write, the sun is setting and THEY SAY a blog written in daylight hours attracts a greater readership than dusk-to-dawn material........BULLSHIT!
Friday 23 November 2012
Thursday 1 November 2012
In all probability........
We live in a world of information overload. Sorting out the wheat from the chaff is never easy particularly when so many of the 'facts' cannot be specified precisely. It is often difficult to make judgements from any set of data but when the information is known to be imprecise, drawing conclusions can be fraught with problems. Let's take the world of statistics and probabilities, starting with the former.
Benjamin Disraeli is attributed by many to have originated the phrase: "There are lies, damned lies, and statistics". Well perhaps before before exploring this statement further, it is worth drawing the distinction between statistics and probabilities. Statistics are numbers that represent facts and as such, deal with certainties, as long as good counting methods are employed. Probabilities, on the other hand, deal with the unknown. So Disraeli's statement is false if the implication is that statistics are a higher form of untruths than 'damned lies'. It is the misuse of statistics, very often linked with probabilities, that can result, intentionally or unintentionally, in something worse than 'damned lies'.
If the residents of a town, who are aged ten or over, are asked to report to a medical centre to have their heights and weights measured, then these measurements can be compared with the criteria for obesity and a statistic of the obesity of the population can be assessed. Let's assume the result was 34% of the population aged ten or over were, at the time the measurements were taken, technically obese. That measurement of 34% is a statistic. Now, if a government bureaucrat decides to use that statistic for other means, for example assessing the probability of obesity in the nation as a whole and publishes a statement to the effect: "it is likely that one in three of the nation's inhabitants over the age of ten, is obese", then the 34% is now a probability rather than a statistic. It would only become a statistic if it was supported by measurements taken of the entire nation's population. An assessment of probability based on the results of one town can be very misleading if the sample that was measured was not truly representative of the country as a whole.
One of the websites that I use for local weather forecasts, provides 'probability of precipitation' information, which is another way of saying the likelihood of rain. There is no indication of how that figure has been computed but there is likely to be a computer algorithm that might use current and historic data to assess the likelihood of rain. Note the last sentence used the words 'likely to be' and 'might use'; that sentence, therefore, has a probability of being correct and likewise a probability of being incorrect - just what can you believe these days?! Returning to the weather forecast, if the probability of rain is 70%, then the probability of no rain is 30%. This means that if I plan my day on the assumption that it is going to rain, then I might be (I've used the word 'might' again!!) very disappointed if it doesn't rain but I can't complain to the forecaster because he or she would point out that there was always a 30% probability of the rain not materialising. So what use is the forecast?!
I suppose our conversations would be very limited if all we communicated were certainties. There are very few certainties and none if we are talking about the future. Also the high probability, low impact events might be interesting but don't change our lives significantly. So if it doesn't rain tomorrow and I planned on it being wet, because the forecaster told me there was a 70% probability of precipitation, then my change of plan might be to do some gardening rather than work in the house. So what?! The real life-changers are the low probability, high impact events, very often not even considered. So if my house was hit and destroyed by a meteorite, oh boy that would be a life changer.
The more I think about probabilities, the more convinced I am that detailed long-term planning of our lives is a waste of time. We should live for the present, trying to improve our actions by learning from the past (positive and negative experiences) and attempt to use the present to make some positive impact on the future. In all probability you will agree with that........but then again, you might not! :-)
Benjamin Disraeli is attributed by many to have originated the phrase: "There are lies, damned lies, and statistics". Well perhaps before before exploring this statement further, it is worth drawing the distinction between statistics and probabilities. Statistics are numbers that represent facts and as such, deal with certainties, as long as good counting methods are employed. Probabilities, on the other hand, deal with the unknown. So Disraeli's statement is false if the implication is that statistics are a higher form of untruths than 'damned lies'. It is the misuse of statistics, very often linked with probabilities, that can result, intentionally or unintentionally, in something worse than 'damned lies'.
If the residents of a town, who are aged ten or over, are asked to report to a medical centre to have their heights and weights measured, then these measurements can be compared with the criteria for obesity and a statistic of the obesity of the population can be assessed. Let's assume the result was 34% of the population aged ten or over were, at the time the measurements were taken, technically obese. That measurement of 34% is a statistic. Now, if a government bureaucrat decides to use that statistic for other means, for example assessing the probability of obesity in the nation as a whole and publishes a statement to the effect: "it is likely that one in three of the nation's inhabitants over the age of ten, is obese", then the 34% is now a probability rather than a statistic. It would only become a statistic if it was supported by measurements taken of the entire nation's population. An assessment of probability based on the results of one town can be very misleading if the sample that was measured was not truly representative of the country as a whole.
One of the websites that I use for local weather forecasts, provides 'probability of precipitation' information, which is another way of saying the likelihood of rain. There is no indication of how that figure has been computed but there is likely to be a computer algorithm that might use current and historic data to assess the likelihood of rain. Note the last sentence used the words 'likely to be' and 'might use'; that sentence, therefore, has a probability of being correct and likewise a probability of being incorrect - just what can you believe these days?! Returning to the weather forecast, if the probability of rain is 70%, then the probability of no rain is 30%. This means that if I plan my day on the assumption that it is going to rain, then I might be (I've used the word 'might' again!!) very disappointed if it doesn't rain but I can't complain to the forecaster because he or she would point out that there was always a 30% probability of the rain not materialising. So what use is the forecast?!
I suppose our conversations would be very limited if all we communicated were certainties. There are very few certainties and none if we are talking about the future. Also the high probability, low impact events might be interesting but don't change our lives significantly. So if it doesn't rain tomorrow and I planned on it being wet, because the forecaster told me there was a 70% probability of precipitation, then my change of plan might be to do some gardening rather than work in the house. So what?! The real life-changers are the low probability, high impact events, very often not even considered. So if my house was hit and destroyed by a meteorite, oh boy that would be a life changer.
The more I think about probabilities, the more convinced I am that detailed long-term planning of our lives is a waste of time. We should live for the present, trying to improve our actions by learning from the past (positive and negative experiences) and attempt to use the present to make some positive impact on the future. In all probability you will agree with that........but then again, you might not! :-)
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