0:00:12.534,0:00:15.630
Back in 2003,

0:00:15.654,0:00:18.163
the UK government carried out a survey.

0:00:19.314,0:00:22.463
And it was a survey that measured[br]levels of numeracy

0:00:22.487,0:00:23.724
in the population.

0:00:23.748,0:00:25.391
And they were shocked to find out

0:00:25.415,0:00:28.779
that for every 100 working age[br]adults in the country,

0:00:28.803,0:00:32.304
47 of them lacked Level 1 numeracy skills.

0:00:32.712,0:00:36.824
Now, Level 1 numeracy skills --[br]that's low-end GCSE score.

0:00:37.230,0:00:40.478
It's the ability to deal with fractions,[br]percentages and decimals.

0:00:40.502,0:00:45.130
So this figure prompted[br]a lot of hand-wringing in Whitehall.

0:00:45.154,0:00:46.782
Policies were changed,

0:00:46.806,0:00:48.528
investments were made,

0:00:48.552,0:00:51.590
and then they ran[br]the survey again in 2011.

0:00:51.614,0:00:53.819
So can you guess[br]what happened to this number?

0:00:55.841,0:00:57.285
It went up to 49.

0:00:57.309,0:00:58.758
(Laughter)

0:00:58.782,0:01:01.231
And in fact, when I reported[br]this figure in the FT,

0:01:01.255,0:01:02.926
one of our readers joked and said,

0:01:02.950,0:01:06.711
"This figure is only shocking[br]to 51 percent of the population."

0:01:06.735,0:01:09.021
(Laughter)

0:01:09.045,0:01:12.202
But I preferred, actually,[br]the reaction of a schoolchild

0:01:12.226,0:01:15.321
when I presented[br]at a school this information,

0:01:15.345,0:01:16.876
who raised their hand and said,

0:01:16.900,0:01:19.416
"How do we know that the person[br]who made that number

0:01:19.440,0:01:21.255
isn't one of the 49 percent either?"

0:01:21.279,0:01:22.533
(Laughter)

0:01:22.557,0:01:26.607
So clearly, there's a numeracy issue,

0:01:26.631,0:01:28.741
because these are[br]important skills for life,

0:01:28.765,0:01:32.632
and a lot of the changes[br]that we want to introduce in this century

0:01:32.656,0:01:35.097
involve us becoming[br]more comfortable with numbers.

0:01:35.121,0:01:36.969
Now, it's not just an English problem.

0:01:36.993,0:01:41.923
OECD this year released some figures[br]looking at numeracy in young people,

0:01:41.947,0:01:44.727
and leading the way, the USA --

0:01:44.751,0:01:49.421
nearly 40 percent of young people[br]in the US have low numeracy.

0:01:49.445,0:01:50.742
Now, England is there too,

0:01:50.766,0:01:55.899
but there are seven OECD countries[br]with figures above 20 percent.

0:01:55.923,0:01:58.682
That is a problem,[br]because it doesn't have to be that way.

0:01:58.706,0:02:00.714
If you look at the far end of this graph,

0:02:00.738,0:02:03.698
you can see the Netherlands and Korea[br]are in single figures.

0:02:04.122,0:02:08.506
So there's definitely a numeracy[br]problem that we want to address.

0:02:08.530,0:02:11.460
Now, as useful as studies like these are,

0:02:11.484,0:02:16.884
I think we risk herding people[br]inadvertently into one of two categories;

0:02:16.908,0:02:18.684
that there are two kinds of people:

0:02:18.708,0:02:23.057
those people that are comfortable[br]with numbers, that can do numbers,

0:02:23.081,0:02:25.317
and the people who can't.

0:02:25.341,0:02:27.442
And what I'm trying[br]to talk about here today

0:02:27.466,0:02:30.508
is to say that I believe[br]that is a false dichotomy.

0:02:30.532,0:02:32.400
It's not an immutable pairing.

0:02:32.424,0:02:36.072
I think you don't have to have[br]tremendously high levels of numeracy

0:02:36.096,0:02:37.824
to be inspired by numbers,

0:02:37.848,0:02:40.957
and that should be the starting point[br]to the journey ahead.

0:02:41.407,0:02:45.718
And one of the ways in which[br]we can begin that journey, for me,

0:02:45.742,0:02:47.468
is looking at statistics.

0:02:47.492,0:02:50.987
Now, I am the first to acknowledge[br]that statistics has got somewhat

0:02:51.011,0:02:52.329
of an image problem.

0:02:52.353,0:02:53.400
(Laughter)

0:02:53.424,0:02:54.956
It's the part of mathematics

0:02:54.980,0:02:58.039
that even mathematicians[br]don't particularly like,

0:02:58.063,0:03:02.075
because whereas the rest of maths[br]is all about precision and certainty,

0:03:02.099,0:03:04.383
statistics is almost the reverse of that.

0:03:04.813,0:03:09.468
But actually, I was a late convert[br]to the world of statistics myself.

0:03:09.492,0:03:11.574
If you'd asked my undergraduate professors

0:03:11.598,0:03:16.357
what two subjects would I be least likely[br]to excel in after university,

0:03:16.381,0:03:19.148
they'd have told you statistics[br]and computer programming,

0:03:19.172,0:03:22.111
and yet here I am, about to show you[br]some statistical graphics

0:03:22.135,0:03:23.337
that I programmed.

0:03:23.765,0:03:25.520
So what inspired that change in me?

0:03:25.544,0:03:29.192
What made me think that statistics[br]was actually an interesting thing?

0:03:29.216,0:03:31.482
It's really because[br]statistics are about us.

0:03:31.889,0:03:34.471
If you look at the etymology[br]of the word statistics,

0:03:34.495,0:03:37.104
it's the science of dealing with data

0:03:37.128,0:03:39.558
about the state or the community[br]that we live in.

0:03:39.582,0:03:42.936
So statistics are about us as a group,

0:03:42.960,0:03:44.635
not us as individuals.

0:03:44.659,0:03:46.129
And I think as social animals,

0:03:46.153,0:03:50.097
we share this fascination about how[br]we as individuals relate to our groups,

0:03:50.121,0:03:51.509
to our peers.

0:03:51.533,0:03:54.643
And statistics in this way[br]are at their most powerful

0:03:54.667,0:03:55.968
when they surprise us.

0:03:56.497,0:03:59.704
And there's been some really wonderful[br]surveys carried out recently

0:03:59.728,0:04:01.450
by Ipsos MORI in the last few years.

0:04:01.474,0:04:04.042
They did some really interesting stuff.

0:04:04.066,0:04:06.774
They did a survey[br]of over 1,000 adults in the UK,

0:04:06.798,0:04:10.978
and said, for every 100 people[br]in England and Wales,

0:04:11.002,0:04:12.872
how many of them are Muslim?

0:04:13.696,0:04:16.342
Now the average answer from this survey,

0:04:16.366,0:04:19.778
which was supposed to be representative[br]of the total population ...

0:04:20.264,0:04:21.970
was 24.

0:04:22.802,0:04:24.178
That's what people thought.

0:04:24.202,0:04:27.841
British people think 24 out of every 100[br]people in the country are Muslim.

0:04:27.865,0:04:31.968
Now, official figures reveal[br]that figure to be about five.

0:04:33.252,0:04:37.239
So there's this big variation[br]between what we think, our perception,

0:04:37.263,0:04:39.301
and the reality as given by statistics.

0:04:39.325,0:04:40.869
And I think that's interesting.

0:04:40.893,0:04:44.183
What could possibly be causing[br]that misperception?

0:04:44.732,0:04:46.586
And I was so thrilled with this study,

0:04:46.610,0:04:50.090
I started to take questions out[br]in presentations. I was referring to it.

0:04:50.114,0:04:51.332
Now, I did a presentation

0:04:51.356,0:04:53.666
at St. Paul's School for Girls[br]in Hammersmith,

0:04:53.690,0:04:55.830
and I had an audience rather like this,

0:04:55.854,0:04:59.722
except it was comprised entirely[br]of sixth-form girls.

0:04:59.746,0:05:02.142
And I said, "Girls,

0:05:03.018,0:05:07.561
how many teenage girls do you think[br]the British public think

0:05:07.585,0:05:09.333
get pregnant every year?"

0:05:09.357,0:05:12.033
And the girls were apoplectic when I said

0:05:12.873,0:05:16.786
the British public think that 15[br]out of every 100 teenage girls

0:05:16.810,0:05:18.103
get pregnant in the year.

0:05:18.849,0:05:21.080
And they had every right to be angry,

0:05:21.104,0:05:23.862
because in fact, I'd have to have[br]closer to 200 dots

0:05:23.886,0:05:25.456
before I could color one in,

0:05:25.480,0:05:27.995
in terms of what[br]the official figures tell us.

0:05:28.019,0:05:31.819
And rather like numeracy,[br]this is not just an English problem.

0:05:31.843,0:05:36.347
Ipsos MORI expanded the survey[br]in recent years to go across the world.

0:05:36.871,0:05:40.121
And so, they asked Saudi Arabians,

0:05:40.145,0:05:42.666
for every 100 adults in your country,

0:05:42.690,0:05:45.563
how many of them are overweight or obese?

0:05:46.746,0:05:52.079
And the average answer from the Saudis[br]was just over a quarter.

0:05:52.622,0:05:53.824
That's what they thought.

0:05:53.848,0:05:56.416
Just over a quarter of adults[br]are overweight or obese.

0:05:56.440,0:06:01.221
The official figures show, actually,[br]it's nearer to three-quarters.

0:06:01.245,0:06:02.701
(Laughter)

0:06:02.725,0:06:05.017
So again, a big variation.

0:06:05.041,0:06:09.487
And I love this one: they asked in Japan,[br]they asked the Japanese,

0:06:09.511,0:06:11.471
for every 100 Japanese people,

0:06:11.495,0:06:14.096
how many of them live in rural areas?

0:06:14.741,0:06:19.642
The average was about a 50-50 split,[br]just over halfway.

0:06:19.666,0:06:23.813
They thought 56 out of every 100[br]Japanese people lived in rural areas.

0:06:23.837,0:06:25.864
The official figure is seven.

0:06:27.179,0:06:31.629
So extraordinary variations,[br]and surprising to some,

0:06:31.653,0:06:34.042
but not surprising to people[br]who have read the work

0:06:34.066,0:06:38.458
of Daniel Kahneman, for example,[br]the Nobel-winning economist.

0:06:38.482,0:06:43.574
He and his colleague, Amos Tversky,[br]spent years researching this disjoint

0:06:43.598,0:06:46.743
between what people perceive[br]and the reality,

0:06:46.767,0:06:50.518
the fact that people are actually[br]pretty poor intuitive statisticians.

0:06:50.542,0:06:52.302
And there are many reasons for this.

0:06:52.326,0:06:55.441
Individual experiences, certainly,[br]can influence our perceptions,

0:06:55.465,0:06:59.423
but so, too, can things like the media[br]reporting things by exception,

0:06:59.447,0:07:01.143
rather than what's normal.

0:07:02.475,0:07:04.601
Kahneman had a nice way[br]of referring to that.

0:07:04.625,0:07:06.710
He said, "We can be blind[br]to the obvious" --

0:07:06.734,0:07:08.372
so we've got the numbers wrong --

0:07:08.396,0:07:10.718
"but we can be blind[br]to our blindness about it."

0:07:10.742,0:07:13.554
And that has enormous[br]repercussions for decision making.

0:07:15.432,0:07:18.284
So at the statistics office[br]while this was all going on,

0:07:18.308,0:07:20.220
I thought this was really interesting.

0:07:20.244,0:07:22.254
I said, this is clearly a global problem,

0:07:22.278,0:07:24.713
but maybe geography is the issue here.

0:07:24.737,0:07:28.646
These were questions that were all about,[br]how well do you know your country?

0:07:28.670,0:07:32.663
So in this case, it's how well[br]do you know 64 million people?

0:07:32.687,0:07:35.419
Not very well, it turns out.[br]I can't do that.

0:07:35.443,0:07:36.767
So I had an idea,

0:07:36.791,0:07:39.914
which was to think about[br]this same sort of approach

0:07:39.938,0:07:42.043
but to think about it[br]in a very local sense.

0:07:42.067,0:07:43.258
Is this a local?

0:07:43.282,0:07:45.223
If we reframe the questions and say,

0:07:45.247,0:07:47.369
how well do you know your local area,

0:07:47.893,0:07:49.996
would your answers be any more accurate?

0:07:51.337,0:07:53.099
So I devised a quiz:

0:07:53.123,0:07:54.982
How well do you know your area?

0:07:55.974,0:07:57.863
It's a simple Web app.

0:07:57.887,0:07:59.070
You put in a post code

0:07:59.094,0:08:01.801
and then it will ask you questions[br]based on census data

0:08:01.825,0:08:03.364
for your local area.

0:08:03.825,0:08:05.948
And I was very conscious[br]in designing this.

0:08:05.972,0:08:10.081
I wanted to make it open[br]to the widest possible range of people,

0:08:10.105,0:08:12.933
not just the 49 percent[br]who can get the numbers.

0:08:12.957,0:08:14.712
I wanted everyone to engage with it.

0:08:14.736,0:08:16.261
So for the design of the quiz,

0:08:16.685,0:08:20.300
I was inspired by the isotypes

0:08:20.324,0:08:22.926
of Otto Neurath from the 1920s and '30s.

0:08:22.950,0:08:27.798
Now, these are methods[br]for representing numbers

0:08:27.822,0:08:29.595
using repeating icons.

0:08:30.060,0:08:33.225
And the numbers are there,[br]but they sit in the background.

0:08:33.249,0:08:35.972
So it's a great way[br]of representing quantity

0:08:35.996,0:08:38.980
without resorting to using terms[br]like "percentage,"

0:08:39.004,0:08:40.234
"fractions" and "ratios."

0:08:40.258,0:08:41.960
So here's the quiz.

0:08:42.730,0:08:44.377
The layout of the quiz is,

0:08:44.401,0:08:47.220
you have your repeating icons[br]on the left-hand side there,

0:08:47.244,0:08:50.367
and a map showing you the area[br]we're asking you questions about

0:08:50.391,0:08:51.558
on the right-hand side.

0:08:51.582,0:08:52.863
There are seven questions.

0:08:52.887,0:08:56.780
Each question, there's a possible answer[br]between zero and a hundred,

0:08:56.804,0:08:58.153
and at the end of the quiz,

0:08:58.177,0:09:01.395
you get an overall score[br]between zero and a hundred.

0:09:01.419,0:09:03.503
And so because this is TEDxExeter,

0:09:03.527,0:09:05.852
I thought we would have[br]a quick look at the quiz

0:09:05.876,0:09:08.185
for the first few questions of Exeter.

0:09:08.209,0:09:09.614
And so the first question is:

0:09:09.638,0:09:12.630
For every 100 people,[br]how many are aged under 16?

0:09:13.204,0:09:16.804
Now, I don't know Exeter very well[br]at all, so I had a guess at this,

0:09:16.828,0:09:19.389
but it gives you an idea[br]of how this quiz works.

0:09:19.413,0:09:23.119
You drag the slider[br]to highlight your icons,

0:09:23.143,0:09:25.378
and then just click "Submit" to answer,

0:09:25.402,0:09:29.065
and we animate away the difference[br]between your answer and reality.

0:09:29.089,0:09:33.164
And it turns out, I was a pretty[br]terrible guess: five.

0:09:33.569,0:09:34.993
How about the next question?

0:09:35.017,0:09:37.173
This is asking about[br]what the average age is,

0:09:37.197,0:09:39.642
so the age at which half[br]the population are younger

0:09:39.666,0:09:41.340
and half the population are older.

0:09:41.364,0:09:44.714
And I thought 35 -- that sounds[br]middle-aged to me.

0:09:44.738,0:09:46.181
(Laughter)

0:09:48.626,0:09:50.732
Actually, in Exeter,[br]it's incredibly young,

0:09:50.756,0:09:55.294
and I had underestimated the impact[br]of the university in this area.

0:09:55.318,0:09:57.349
The questions get harder[br]as you go through.

0:09:57.373,0:09:59.756
So this one's now asking[br]about homeownership:

0:10:00.375,0:10:04.074
For every 100 households, how many[br]are owned with a mortgage or loan?

0:10:04.098,0:10:05.378
And I hedged my bets here,

0:10:05.402,0:10:08.500
because I didn't want to be[br]more than 50 out on the answer.

0:10:08.524,0:10:10.024
(Laughter)

0:10:10.568,0:10:13.034
And actually, these get harder,[br]these questions,

0:10:13.058,0:10:15.917
because when you're in an area,[br]when you're in a community,

0:10:15.941,0:10:21.191
things like age -- there are clues[br]to whether a population is old or young.

0:10:21.215,0:10:23.560
Just by looking around[br]the area, you can see it.

0:10:23.584,0:10:26.975
Something like homeownership[br]is much more difficult to see,

0:10:26.999,0:10:29.607
so we revert to our own heuristics,

0:10:29.631,0:10:34.082
our own biases about how many people[br]we think own their own homes.

0:10:34.106,0:10:37.756
Now the truth is,[br]when we published this quiz,

0:10:37.780,0:10:41.317
the census data that it's based on[br]was already a few years old.

0:10:41.341,0:10:45.259
We've had online applications[br]that allow you to put in a post code

0:10:45.283,0:10:47.377
and get statistics back for years.

0:10:47.521,0:10:48.710
So in some senses,

0:10:48.734,0:10:52.283
this was all a little bit old[br]and not necessarily new.

0:10:52.307,0:10:55.946
But I was interested to see[br]what reaction we might get

0:10:55.970,0:10:58.687
by gamifying the data[br]in the way that we have,

0:10:58.711,0:11:00.118
by using animation

0:11:00.142,0:11:03.890
and playing on the fact[br]that people have their own preconceptions.

0:11:05.418,0:11:09.001
It turns out, the reaction was, um ...

0:11:10.038,0:11:12.584
was more than I could have hoped for.

0:11:13.230,0:11:16.611
It was a long-held ambition of mine[br]to bring down a statistics website

0:11:16.635,0:11:18.043
due to public demand.

0:11:18.067,0:11:19.867
(Laughter)

0:11:19.891,0:11:23.355
This URL contains the words[br]"statistics," "gov" and "UK,"

0:11:23.379,0:11:26.621
which are three of people's least[br]favorite words in a URL.

0:11:26.645,0:11:30.630
And the amazing thing about this[br]was that the website came down

0:11:30.654,0:11:32.747
at quarter to 10 at night,

0:11:32.771,0:11:35.982
because people were actually[br]engaging with this data

0:11:36.006,0:11:37.545
of their own free will,

0:11:37.569,0:11:39.088
using their own personal time.

0:11:39.328,0:11:41.315
I was very interested to see

0:11:41.339,0:11:45.052
that we got something like[br]a quarter of a million people

0:11:45.076,0:11:48.348
playing the quiz within the space[br]of 48 hours of launching it.

0:11:48.372,0:11:52.299
And it sparked an enormous discussion[br]online, on social media,

0:11:52.323,0:11:54.424
which was largely dominated

0:11:54.448,0:11:58.377
by people having fun[br]with their misconceptions,

0:11:58.401,0:12:01.460
which is something that[br]I couldn't have hoped for any better,

0:12:01.484,0:12:02.644
in some respects.

0:12:02.668,0:12:05.894
I also liked the fact that people started[br]sending it to politicians.

0:12:05.918,0:12:08.507
How well do you know the area[br]you claim to represent?

0:12:08.531,0:12:09.693
(Laughter)

0:12:09.717,0:12:11.277
And then just to finish,

0:12:12.172,0:12:14.502
going back to the two kinds of people,

0:12:14.526,0:12:16.783
I thought it would be[br]really interesting to see

0:12:16.807,0:12:19.622
how people who are good with numbers[br]would do on this quiz.

0:12:19.646,0:12:22.662
The national statistician[br]of England and Wales, John Pullinger,

0:12:22.686,0:12:24.759
you would expect he would be pretty good.

0:12:25.704,0:12:28.284
He got 44 for his own area.

0:12:28.308,0:12:30.645
(Laughter)

0:12:30.669,0:12:34.589
Jeremy Paxman -- admittedly,[br]after a glass of wine ...

0:12:35.979,0:12:37.129
36.

0:12:37.301,0:12:38.762
Even worse.

0:12:38.786,0:12:41.548
It just shows you that the numbers[br]can inspire us all.

0:12:41.572,0:12:42.832
They can surprise us all.

0:12:42.985,0:12:45.040
So very often, we talk about statistics

0:12:45.064,0:12:47.050
as being the science of uncertainty.

0:12:47.074,0:12:48.857
My parting thought for today is:

0:12:48.881,0:12:51.917
actually, statistics is the science of us.

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And that's why we should[br]be fascinated by numbers.

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Thank you very much.

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(Applause)