posted 3rd January 2022
How can debaters best use statistics?
Here are some ground rules:
1. Only use accurate statistics
If you are researching for a long prep debate, check and double check for accuracy. Make sure your information comes from a reputable source. The Office for National Statistics will certainly have more reliable numbers for vaccination take up than a Facebook page dedicated to proving that the Covid vaccine is an evil plot by Bill Gates to plant a microchip in your brain.
If you are speaking in a short prep debate, where you cannot use the internet in preparation time, and you have a vague recollection of a statistic which you think you might use to help your case, don't. Only use statistics which you are 100% certain are accurate.
One way of having up to date numbers to hand in short prep debates, given that hard copy resources are permitted, is to keep a debating notebook, in which, between debates, you note down statistics and other relevant data, facts and arguments related to likely and current debating issues. As well as providing you with a legitimate and accurate data source, this is an excellent way of remaining engaged with topical issues.
Above all, don't make stuff up. Your opponents may not be able to check your facts during the debate, but the judge can, and your wild assertion that 17 million people have lost their jobs because of the Covid lockdown can and will be found out, losing you a lot of marks.
2. Be sparing
I've listened as a judge to many speeches which seem to consist largely of a long list of numbers. They may show that the speaker has been very thorough in her research, but they nearly always end up confusing the listeners, and distracting them from the point of the argument. Better to have one or two really significant and meaningful numbers which back your argument. Less is more.
3. Prioritise the argument
Your job is to make a stronger argument than your opponents, not to produce more data than them. Your arguments must take precedence over your data, which are only of any use if they support your arguments.
4. Think about how it sounds
Here are some statistics about Covid:
A In the last week of 2021, 6.7% of the UK population tested positive for Covid.
B In the last week of 2021, one in 15 people in the UK tested positive for Covid.
C In the last week of 2021, 3.7 million people in the UK tested positive for Covid.
D In the last week of 2021, 93.3% of people in the UK didn't test positive for Covid.
They're all the same statistic. But they sound different, depending on how they are expressed. A makes the problem of Covid sound relatively small. B makes it sound worse. C makes it sound massive. D reminds us that Covid still only affects a minority. If you are arguing against further restrictions, you should use A or, even better, D. If you are arguing for further restrictions, use B, or even better, C. This is a perfectly legitimate tactic.
5. Only use statistics that refer to facts, never ones that refer to opinions.
Opinion polls and election results may be of interest in telling us what people think or feel about something, but they don't prove anything. Saying that 60% of people are against further Covid restrictions might prove that these restrictions are unpopular; it doesn't prove that they're the wrong thing to do.
How can statistics support your argument?
There are really only two ways in which statistics can support an argument in a debate.
The first is by giving information about the status quo (the current situation), in the interests of either showing that it is bad and needs to be changed (if you are the proposition), or that it is good and does not need to be changed (if you are the opposition).
So, in a debate on the motion 'This house would make it compulsory to show proof of vaccination before being allowed to enter an enclosed public space', the proposition might cite the fact that 1,110,159 people have tested positive for Covid to underline the gravity of the situation and the need for drastic measures; the opposition might reply that 98.6% of the population have not tested positive for Covid, and that therefore there is no need for drastic intervention.
The second is by providing evidence of causality; that is, that one thing has led or is likely to lead to another. If your numbers show that A has led to B, and B is a bad thing, this helps prove that A is a problem that needs to be addressed. If your numbers show that A has led to B, and B is a good thing, this helps prove that we should have more of A.
So, in the motion on vaccine passports, the proposition might point to the fact that while only 9% of the population remain unvaccinated, 60% of patients in intensive care with Covid are unvaccinated. From these two numbers, it is reasonable to extrapolate that remaining unvaccinated (A) greatly increases your risk of ending up in hospital with Covid (B). This makes for a strong argument in favour of putting maximum pressure on people to get vaccinated to prevent the NHS from being overwhelmed.
The opposition, however, could reply with some different statistics. To take one city: in Manchester, 50% of people in poorer areas remain unjabbed; in more affluent areas, it is 20%. White people in the city have an 80% uptake of the vaccine; amongst people from a Caribbean background, it is just 52%. From these numbers, you can extrapolate that vaccine refusal (B) is likely to be prompted not by insane theories about Bill Gates and microchips, but by social and racial exclusion (A), and you can therefore argue that vaccine passports, which will exclude the unvaccinated still further, are likely to be counter-productive. A more effective way of increasing vaccine uptake will be to direct resources to engagement and education in marginalised communities, thereby dealing with the problem of exclusion (A), which is what is causing vaccine refusal (B).
To learn more about how to understand, and how to use, statistics, I warmly recommend Tim Harford's excellent book How To Make the World Add Up, and also the BBC Radio 4 show (hosted by Tim Harford) More or Less, which looks each week at statistics in the news and what they really mean.
