Free Critical thinking for Students by Roy van den Brink-Budgen Page A

One of the evaluation questions we might want to ask is population size. Perhaps the UK population size is sufficiently large to (partly) explain the UK’s position in the European league table. A quick look at the numbers suggests not.
     
    The population of the UK is 59.8m; that of Italy is 58.1m; France is 60.7m; Germany is 82.7m; with the only one noticeably lower than the UK being Spain with 43.4m.
     
    There would have been little point translating these numbers into percentages: the numbers give us the information we need to see that it is not population size that in itself explains what’s going on. (You still, of course, need to consider alternative explanations in relation to the inference. There are quite a few.)
     
    Another example in which numbers themselves give us lots of information is the amount of time spent watching TV. The US tops the international league table here with an average daily household viewing of a little over eight hours. (Second is Turkey with five hours, with the UK way down the table on only three.) There would be no point in translating hours per day into a different measure, given that the number of hours per day does not change.
     
    However, sometimes numbers might express something, but we’re not sure what. For example, we know that the number of aid workers killed in 2008 whilst on duty was 140. In 2007, it was 75; in 2006 it was 84. So there was a big increase in aid workers (especially locally-recruited ones) being killed whilst working in 2008. Is this significant? Here we would need to know whether the number of aid workers has increased overall before we could infer something like ‘the risk of death for aid workers has increased’.
     
    Sometimes there’s a further way of expressing the possible significance of a numerical claim. This is in the form of a rate. A percentage is a type of rate, expressed as a proportion per hundred. But we can find rates expressed as proportions of larger (sometimes much larger) numbers. When we are dealing with very large numbers, a rate (say, per 10,000, 100,000, or more) makes the possible significance of the information more approachable.
     
    For example, does it tell us very much to read that the US spent $607.3 billion on defence in 2008? It tells us something because, by any standards, that’s a lot of money. Is this figure given greater significance when we see that this amount represented 41.5 per cent of the total spent on defence in the world? Probably yes, because we can see that, given this percentage, the US will realistically be the biggest spender on defence of any country in the world.
     
    But there’s another measure which gives us a different significance. This is the amount spent on defence in $000s per person in a country’s population. Using that rate measure, the US is not top of the league table. This position is held by Israel. Though Israel spends (only) $16.2 billion on defence, this represents about $2,300 per person in the country. (The US spends almost $2000 per person.) This league table of spending per person creates a very different picture from the overall amount and the percentage figures. For example, China is second in the list of percentage of global defence spending (with 5.8 per cent of all spending) but features nowhere in the top 15 spenders by rate per head of population (because of its massive population). Using this rate measure, a country like Brunei appears in the premier league of defence spenders, though it spends only $0.3 billion on defence.
     
    Another rate that can be used is that per person in a group or country. Using this measure shows us that Greece heads the international cigarette smoking league table, with a little over eight cigarettes a day being smoked per person. At one level, this tells us a lot, although using this particular measure doesn’t tell us everything. For example, the French come out 62nd in the league table, with only a little over two cigarettes per person.