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Alan Smith: Why you should love statistics
Alan Smith: Hvorfor man burde elske statistik
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Tror du, at du er god til at gætte statistiske fakta? Så tro om igen. Hvad enten vi anser os selv som matematikere eller ej, så er vores evne til at forstå og arbejde med tal stærkt begrænset, siger eksperten i data-visualisering, Alan Smith. I dette herlige foredrag, udforsker Smith uoverensstemmelsen mellem hvad vi ved og hvad vi tror vi ved.
Alan Smith - Data visualisation editor
Alan Smith uses interactive graphics and statistics to breathe new life into how data is presented. Full bio
Alan Smith uses interactive graphics and statistics to breathe new life into how data is presented. Full bio
Double-click the English transcript below to play the video.
00:12
Back in 2003,
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Tilbage i 2003,
00:15
the UK government carried out a survey.
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gennemførte den britiske regering
en undersøgelse,
en undersøgelse,
00:19
And it was a survey that measured
levels of numeracy
levels of numeracy
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der målte regnefærdigheden
00:22
in the population.
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i befolkningen.
00:23
And they were shocked to find out
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Og de var rystet over at se,
00:25
that for every 100 working age
adults in the country,
adults in the country,
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at for hver 100 erhvervsaktive voksne,
00:28
47 of them lacked Level 1 numeracy skills.
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manglede 47 af dem
niveau 1-regnefærdigheder.
niveau 1-regnefærdigheder.
00:32
Now, Level 1 numeracy skills --
that's low-end GCSE score.
that's low-end GCSE score.
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Niveau 1-regnefærdighed --
det er en lav GCSE-score.
det er en lav GCSE-score.
00:37
It's the ability to deal with fractions,
percentages and decimals.
percentages and decimals.
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Det er evnen til at regne med brøker,
procenter og decimaler.
procenter og decimaler.
00:40
So this figure prompted
a lot of hand-wringing in Whitehall.
a lot of hand-wringing in Whitehall.
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Dette tal skabte en masse hændervridning
i Whitehall.
i Whitehall.
00:45
Policies were changed,
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Politikker blev ændret,
00:46
investments were made,
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investeringer blev foretaget.
00:48
and then they ran
the survey again in 2011.
the survey again in 2011.
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Derefter udførte man undersøgelsen
igen i 2011.
igen i 2011.
00:51
So can you guess
what happened to this number?
what happened to this number?
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Kan I gætte, hvad der skete med dette tal?
00:56
It went up to 49.
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Det gik op til 49.
00:57
(Laughter)
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(Latter)
00:58
And in fact, when I reported
this figure in the FT,
this figure in the FT,
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Og da jeg skrev om dette tal
i Financial Times,
i Financial Times,
01:01
one of our readers joked and said,
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spurgte en af vore læsere og sagde:
01:03
"This figure is only shocking
to 51 percent of the population."
to 51 percent of the population."
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"Dette tal er kun chokerende
for 51 procent af befolkningen."
for 51 procent af befolkningen."
01:06
(Laughter)
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(Latter)
01:09
But I preferred, actually,
the reaction of a schoolchild
the reaction of a schoolchild
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Men jeg foretrak reaktionen
fra en skoleelev,
fra en skoleelev,
01:12
when I presented
at a school this information,
at a school this information,
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da jeg præsenterede
denne information på en skole.
denne information på en skole.
01:15
who raised their hand and said,
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Han rejste sin hånd og spurgte:
01:17
"How do we know that the person
who made that number
who made that number
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"Hvordan kan vi vide, at ham,
der regnede tallet ud,
der regnede tallet ud,
01:19
isn't one of the 49 percent either?"
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ikke også var en af de 49 procent?"
01:21
(Laughter)
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(Latter)
01:22
So clearly, there's a numeracy issue,
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Det er klart, at der er et problem
med regnefærdigheden,
med regnefærdigheden,
01:26
because these are
important skills for life,
important skills for life,
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fordi dette er
en vigtig færdighed i livet.
en vigtig færdighed i livet.
01:28
and a lot of the changes
that we want to introduce in this century
that we want to introduce in this century
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Mange af de forandringer, som vi gerne
vil gennemføre i dette århundrede
vil gennemføre i dette århundrede
01:32
involve us becoming
more comfortable with numbers.
more comfortable with numbers.
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involverer, at vi bliver
mere komfortable med tal.
mere komfortable med tal.
01:35
Now, it's not just an English problem.
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Det er ikke bare et engelsk problem.
01:37
OECD this year released some figures
looking at numeracy in young people,
looking at numeracy in young people,
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OECD udgav i år nogle tal
om regnefærdighed hos unge,
om regnefærdighed hos unge,
01:42
and leading the way, the USA --
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og forrest lå USA
01:44
nearly 40 percent of young people
in the US have low numeracy.
in the US have low numeracy.
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med næsten 40 procent af unge,
som har ringe regnefærdigheder.
som har ringe regnefærdigheder.
01:49
Now, England is there too,
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England er der også,
01:50
but there are seven OECD countries
with figures above 20 percent.
with figures above 20 percent.
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men der er syv OECD-lande med
værdier over 20 procent.
værdier over 20 procent.
01:56
That is a problem,
because it doesn't have to be that way.
because it doesn't have to be that way.
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Det er et problem, fordi det ikke
behøver at være sådan.
behøver at være sådan.
01:59
If you look at the far end of this graph,
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Ser man på den anden ende
af denne graf,
af denne graf,
02:01
you can see the Netherlands and Korea
are in single figures.
are in single figures.
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kan man se Holland og Korea
med ét ciffer-størrelser.
med ét ciffer-størrelser.
02:04
So there's definitely a numeracy
problem that we want to address.
problem that we want to address.
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Der er et problem med regnefærdigheden,
som der skal gøres noget ved.
som der skal gøres noget ved.
02:09
Now, as useful as studies like these are,
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Selvom disse undersøgelser er nyttige,
02:12
I think we risk herding people
inadvertently into one of two categories;
inadvertently into one of two categories;
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tror jeg, at vi risikerer uforvarende
at putte folk i én af to kategorier;
at putte folk i én af to kategorier;
02:17
that there are two kinds of people:
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at der er to slags mennesker:
02:19
those people that are comfortable
with numbers, that can do numbers,
with numbers, that can do numbers,
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de mennesker, der er komfortable med tal,
som kan regne med tal,
som kan regne med tal,
02:24
and the people who can't.
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og de mennesker, der ikke kan.
02:26
And what I'm trying
to talk about here today
to talk about here today
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Og det, jeg forsøger at sige,
02:28
is to say that I believe
that is a false dichotomy.
that is a false dichotomy.
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er, at jeg tror,
at det er en falsk modsætning.
at det er en falsk modsætning.
02:31
It's not an immutable pairing.
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Det er ikke en uforanderlig parring.
02:33
I think you don't have to have
tremendously high levels of numeracy
tremendously high levels of numeracy
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Jeg tror ikke, man behøver
en voldsom god talforståelse
en voldsom god talforståelse
02:37
to be inspired by numbers,
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for at interessere sig for tal,
02:38
and that should be the starting point
to the journey ahead.
to the journey ahead.
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og det bør være udgangspunktet for,
hvad vi gør fremover.
hvad vi gør fremover.
02:42
And one of the ways in which
we can begin that journey, for me,
we can begin that journey, for me,
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Og en af måderne, hvorpå vi kan gøre
tal interessante, er, for mig,
tal interessante, er, for mig,
02:46
is looking at statistics.
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at se på statistikken.
02:48
Now, I am the first to acknowledge
that statistics has got somewhat
that statistics has got somewhat
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Nu er jeg den første til at erkende,
at statistikken
at statistikken
02:51
of an image problem.
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har lidt
af et imageproblem.
af et imageproblem.
02:53
(Laughter)
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(Latter)
02:54
It's the part of mathematics
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Det er den del af matematikken,
02:55
that even mathematicians
don't particularly like,
don't particularly like,
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som selv matematikere ikke
holder ret meget af,
holder ret meget af,
02:59
because whereas the rest of maths
is all about precision and certainty,
is all about precision and certainty,
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fordi, mens resten af matematikken
handler om præcision og sikkerhed,
handler om præcision og sikkerhed,
03:03
statistics is almost the reverse of that.
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er statistik næsten det modsatte.
03:05
But actually, I was a late convert
to the world of statistics myself.
to the world of statistics myself.
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Jeg var faktisk sen til at konvertere
til statistikken.
til statistikken.
03:10
If you'd asked my undergraduate professors
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Hvis man havde spurgt mine professorer,
03:12
what two subjects would I be least likely
to excel in after university,
to excel in after university,
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om hvilke to emner jeg næppe
ville udmærke mig i efter universitetet,
ville udmærke mig i efter universitetet,
03:17
they'd have told you statistics
and computer programming,
and computer programming,
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ville de have sagt statistik og
programmering af computere,
programmering af computere,
03:20
and yet here I am, about to show you
some statistical graphics
some statistical graphics
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og alligevel er jeg ved
at vise jer statistiske grafikker,
at vise jer statistiske grafikker,
03:23
that I programmed.
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som jeg har programmeret.
03:24
So what inspired that change in me?
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Hvad fik mig til den forandring?
03:26
What made me think that statistics
was actually an interesting thing?
was actually an interesting thing?
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Hvad fik mig til at tænke,
at statistikken faktisk er interessant?
at statistikken faktisk er interessant?
03:30
It's really because
statistics are about us.
statistics are about us.
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Det var fordi statistik handler om os.
03:32
If you look at the etymology
of the word statistics,
of the word statistics,
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Hvis man ser på etymologien
for ordet statistik,
for ordet statistik,
03:35
it's the science of dealing with data
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er det videnskaben om data,
03:38
about the state or the community
that we live in.
that we live in.
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om staten eller det samfund,
som vi lever i.
som vi lever i.
03:40
So statistics are about us as a group,
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Så statistik drejer sig om os
som en gruppe,
som en gruppe,
03:43
not us as individuals.
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ikke os som individer.
03:45
And I think as social animals,
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Og jeg tror, som sociale dyr,
03:47
we share this fascination about how
we as individuals relate to our groups,
we as individuals relate to our groups,
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vi deler denne interesse i, hvordan vi er,
i forhold til vore grupper,
i forhold til vore grupper,
03:51
to our peers.
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til vore jævnaldrende.
03:52
And statistics in this way
are at their most powerful
are at their most powerful
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Og statistik er på denne måde
mest kraftfuldt,
mest kraftfuldt,
03:55
when they surprise us.
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når den overrasker os.
03:57
And there's been some really wonderful
surveys carried out recently
surveys carried out recently
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Der er blevet lavet nogle
vidunderlige undersøgelser for nyligt
vidunderlige undersøgelser for nyligt
04:00
by Ipsos MORI in the last few years.
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af Ipsos MORI i de sidste par år.
04:02
They did a survey of over
1,000 adults in the UK,
1,000 adults in the UK,
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De undersøgte over
1.000 voksne i Storbritannien.
1.000 voksne i Storbritannien.
04:05
and said, for every 100 people
in England and Wales,
in England and Wales,
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Man spurgte, "For hver 100 mennesker
i England og Wales,
i England og Wales,
04:08
how many of them are Muslim?
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hvor mange af dem er muslimer?"
04:10
Now the average answer from this survey,
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Det gennemsnitlige svar
fra denne undersøgelse,
fra denne undersøgelse,
04:13
which was supposed to be representative
of the total population, was 24.
of the total population, was 24.
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som skulle repræsentere
den samlede befolkning, var 24.
den samlede befolkning, var 24.
04:16
That's what people thought.
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Det er, hvad folk tænker.
04:20
British people think 24 out of every 100
people in the country are Muslim.
people in the country are Muslim.
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Britter tror at 24 ud
af 100 mennesker er muslimer.
af 100 mennesker er muslimer.
04:24
Now, official figures reveal
that figure to be about five.
that figure to be about five.
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Det officielle tal viser,
at tallet er omkring fem.
at tallet er omkring fem.
04:29
So there's this big variation
between what we think, our perception,
between what we think, our perception,
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Der er en stor forskel mellem,
hvad vi tror,
hvad vi tror,
04:33
and the reality as given by statistics.
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og den statistiske virkelighed.
04:35
And I think that's interesting.
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Jeg synes, det er interessant.
04:37
What could possibly be causing
that misperception?
that misperception?
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Hvad kunne være årsagen
til denne fejlopfattelse?
til denne fejlopfattelse?
04:41
And I was so thrilled with this study,
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Jeg var så begejstret over det,
04:43
I started to take questions out
in presentations. I was referring to it.
in presentations. I was referring to it.
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at jeg begyndte at stille spørgsmål ved
mine foredrag. Jeg fortalte om det.
mine foredrag. Jeg fortalte om det.
04:46
Now, I did a presentation
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Jeg gav et foredrag
04:47
at St. Paul's School for Girls
in Hammersmith,
in Hammersmith,
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på St. Pauls School for Girls
i Hammersmith,
i Hammersmith,
04:50
and I had an audience rather like this,
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og jeg havde et publikum magen til jer,
04:52
except it was comprised entirely
of sixth-form girls.
of sixth-form girls.
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bortset fra, at det udelukkende
bestod af piger i 10. klasse.
bestod af piger i 10. klasse.
04:56
And I said, "Girls,
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Og jeg spurgte, "Piger,
04:59
how many teenage girls do you think
the British public think
the British public think
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hvor mange teenagepiger tror I,
at den britiske offentlighed mener
at den britiske offentlighed mener
05:04
get pregnant every year?"
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bliver gravid hvert år?"
05:05
And the girls were apoplectic when I said
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Og pigerne blev rasende, da jeg sagde,
05:09
the British public think that 15
out of every 100 teenage girls
out of every 100 teenage girls
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den britiske offentlighed mener,
at 15 ud af hver 100 teenagepiger
at 15 ud af hver 100 teenagepiger
05:13
get pregnant in the year.
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bliver gravide hvert år.
05:15
And they had every right to be angry,
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Og de havde god grund til at være vred,
05:17
because in fact, I'd have to have
closer to 200 dots
closer to 200 dots
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fordi jeg skulle bruge
flere end 200 prikker,
flere end 200 prikker,
05:20
before I could color one in,
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før jeg kunne farve én,
05:22
in terms of what
the official figures tell us.
the official figures tell us.
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til at vise, hvad de officielle tal siger.
05:24
And rather like numeracy,
this is not just an English problem.
this is not just an English problem.
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Ligesom regnefærdighed,
er dette ikke bare et engelsk problem.
er dette ikke bare et engelsk problem.
05:28
Ipsos MORI expanded the survey
in recent years to go across the world.
in recent years to go across the world.
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Ipsos MORI udvidede undersøgelsen
med mange lande.
med mange lande.
05:32
And so, they asked Saudi Arabians,
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De spurgte de saudiske arabere:
05:35
for every 100 adults in your country,
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"For hver 100 voksne i dit land,
05:38
how many of them are overweight or obese?
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hvor mange af dem er
overvægtige eller fede?"
overvægtige eller fede?"
05:42
And the average answer from the Saudis
was just over a quarter.
was just over a quarter.
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Det gennemsnitlige svar fra saudierne var
lidt over en fjerdedel.
lidt over en fjerdedel.
05:48
That's what they thought.
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Det er, hvad de troede.
05:49
Just over a quarter of adults
are overweight or obese.
are overweight or obese.
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Lidt over en fjerdedel
var overvægtige eller fede.
var overvægtige eller fede.
05:52
The official figures show, actually,
it's nearer to three-quarters.
it's nearer to three-quarters.
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De officielle tal viser faktisk,
at det er tættere på tre fjerdedele.
at det er tættere på tre fjerdedele.
05:57
(Laughter)
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(Latter)
05:58
So again, a big variation.
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Så igen, en stor forskel.
06:00
And I love this one: they asked in Japan,
they asked the Japanese,
they asked the Japanese,
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Jeg elsker denne her. De spurgte i Japan:
06:05
for every 100 Japanese people,
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"For hver 100 japanere,
06:07
how many of them live in rural areas?
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hvor mange af dem bor i landdistrikterne?"
06:10
The average was about a 50-50 split,
just over halfway.
just over halfway.
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Den gennemsnitlige svar var
omkring 50-50, lidt over halvvejs.
omkring 50-50, lidt over halvvejs.
06:15
They thought 56 out of every 100
Japanese people lived in rural areas.
Japanese people lived in rural areas.
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De troede, at 56 ud af hver 100 japanere
levede i landdistrikterne.
levede i landdistrikterne.
06:19
The official figure is seven.
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Det officielle tal er syv.
06:22
So extraordinary variations,
and surprising to some,
and surprising to some,
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Ekstraordinære forskelle,
og overraskende for nogle,
og overraskende for nogle,
06:26
but not surprising to people
who have read the work
who have read the work
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men ikke overraskende for folk,
som har læst
som har læst
06:29
of Daniel Kahneman, for example,
the Nobel-winning economist.
the Nobel-winning economist.
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Daniel Kahnemans arbejde:
Nobel-prismodtager i økonomi.
Nobel-prismodtager i økonomi.
06:33
He and his colleague, Amos Tversky,
spent years researching this disjoint
spent years researching this disjoint
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Han og hans kollega, Amos Tversky,
brugte år på undersøgelser af denne
brugte år på undersøgelser af denne
06:38
between what people perceive
and the reality,
and the reality,
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uoverensstemmelse mellem,
hvad folk oplever og virkelighededen.
hvad folk oplever og virkelighededen.
06:41
the fact that people are actually
pretty poor intuitive statisticians.
pretty poor intuitive statisticians.
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Det faktum, at folk faktisk er
temmelig dårlige intuitive statistikere.
temmelig dårlige intuitive statistikere.
06:45
And there are many reasons for this.
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Og der er mange grunde til dette.
06:47
Individual experiences, certainly,
can influence our perceptions,
can influence our perceptions,
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Individuelle erfaringer kan i hvert fald
påvirke vore opfattelser.
påvirke vore opfattelser.
06:50
but so, too, can things like the media
reporting things by exception,
reporting things by exception,
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Men også det, at medierne skriver
om det usædvanlige,
om det usædvanlige,
06:54
rather than what's normal.
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snarere end hvad der er normalt.
06:56
Kahneman had a nice way
of referring to that.
of referring to that.
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Kahneman udtrykte det på en pæn måde.
06:59
He said, "We can be blind
to the obvious" --
to the obvious" --
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Han sagde: "Vi kan være blinde
overfor det indlysende" --
overfor det indlysende" --
07:01
so we've got the numbers wrong --
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så vi tror på forkerte tal --
07:02
"but we can be blind
to our blindness about it."
to our blindness about it."
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"men vi kan være blinde
overfor vores blindhed."
overfor vores blindhed."
07:05
And that has enormous
repercussions for decision making.
repercussions for decision making.
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Det har enorme konsekvenser
for beslutningstagning.
for beslutningstagning.
07:08
So at the statistics office
while this was all going on,
while this was all going on,
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Dengang syntes jeg,
07:11
I thought this was really interesting.
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at dette var virkeligt interessant.
07:13
I said, this is clearly a global problem,
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Jeg sagde, at dette er et globalt problem,
07:15
but maybe geography is the issue here.
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men måske er det geografien,
der er problemet her.
der er problemet her.
07:17
These were questions that were all about,
how well do you know your country?
how well do you know your country?
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Spørgsmålene drejede sig om,
hvor godt kender du dit land?
hvor godt kender du dit land?
07:21
So in this case, it's how well
do you know 64 million people?
do you know 64 million people?
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Sagt på en anden måde:
Hvor godt kender du 64 millioner mennesker?
Hvor godt kender du 64 millioner mennesker?
07:25
Not very well, it turns out.
I can't do that.
I can't do that.
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Ikke særlig godt viste det sig.
Jeg kunne ikke gøre det.
Jeg kunne ikke gøre det.
07:28
So I had an idea,
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Så jeg fik en idé,
07:29
which was to think about
this same sort of approach
this same sort of approach
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som var, at have samme slags tilgang,
07:32
but to think about it
in a very local sense.
in a very local sense.
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men at sætte det i
en meget lokal sammenhæng.
en meget lokal sammenhæng.
07:35
Is this a local?
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Er det om det lokale?
07:36
If we reframe the questions and say,
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Hvis vi omformulerer og spørger,
07:38
how well do you know your local area,
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hvor godt kender du dit lokalområde,
07:40
would your answers be any more accurate?
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ville svarene så blive mere præcise?
07:43
So I devised a quiz:
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Så jeg udtænkte en quiz:
07:45
How well do you know your area?
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Hvor godt kender du dit område?
07:48
It's a simple Web app.
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Det er en simpel web-app.
07:50
You put in a post code
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Man skriver et postnummer,
07:51
and then it will ask you questions
based on census data
based on census data
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og så stiller den spørgsmål
baseret på folketællingsdata
baseret på folketællingsdata
07:54
for your local area.
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for lokalområdet.
07:56
And I was very conscious
in designing this.
in designing this.
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Jeg var meget bevidst om designet.
07:58
I wanted to make it open
to the widest possible range of people,
to the widest possible range of people,
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Jeg ønskede at gøre det åbent for
det bredeste udvalg af befolkningen.
det bredeste udvalg af befolkningen.
08:02
not just the 49 percent
who can get the numbers.
who can get the numbers.
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Ikke bare de 49 procent, der kan regne.
08:05
I wanted everyone to engage with it.
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Jeg ønskede at alle deltog i det.
08:07
So for the design of the quiz,
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Så til udformningen af quizzen,
08:08
I was inspired by the isotypes
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blev jeg inspireret af isotyperne
08:12
of Otto Neurath from the 1920s and '30s.
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af Otto Neurath fra 1920'erne og 30'erne.
08:15
Now, these are methods
for representing numbers
for representing numbers
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Det er metoder til repræsentere tal
08:19
using repeating icons.
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ved hjælp gentagne ikoner.
08:21
And the numbers are there,
but they sit in the background.
but they sit in the background.
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Tallene er der,
men de findes i baggrunden.
men de findes i baggrunden.
08:24
So it's a great way
of representing quantity
of representing quantity
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Det er en fantastisk måde
at repræsentere en mængde
at repræsentere en mængde
08:27
without resorting to using terms
like "percentage,"
like "percentage,"
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uden at ty til at bruge
udtryk som "procent",
udtryk som "procent",
08:30
"fractions" and "ratios."
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"fraktioner" og "nøgletal".
08:31
So here's the quiz.
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Her er quizzen.
08:34
The layout of the quiz is,
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Layoutet af quizzen er,
08:35
you have your repeating icons
on the left-hand side there,
on the left-hand side there,
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man har de gentage ikoner
på venstre side,
på venstre side,
08:38
and a map showing you the area
we're asking you questions about
we're asking you questions about
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og et kort, der viser dig det område,
vi stiller spørgsmål til
vi stiller spørgsmål til
08:41
on the right-hand side.
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på højre side.
08:43
There are seven questions.
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Der er syv spørgsmål.
08:44
Each question, there's a possible answer
between zero and a hundred,
between zero and a hundred,
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For hvert spørgsmål, er der et muligt svar
mellem nul og hundrede,
mellem nul og hundrede,
08:48
and at the end of the quiz,
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og i slutningen af quizzen
08:49
you get an overall score
between zero and a hundred.
between zero and a hundred.
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får du en samlet score
mellem nul og hundrede.
mellem nul og hundrede.
08:52
And so because this is TEDxExeter,
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Og så fordi dette er TEDxExeter,
08:55
I thought we would have
a quick look at the quiz
a quick look at the quiz
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tænkte jeg, vi tager
et hurtigt kig på quizzen
et hurtigt kig på quizzen
08:57
for the first few questions of Exeter.
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for de første par spørgsmål af Exeter.
08:59
And so the first question is:
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Så det første spørgsmål er:
09:01
For every 100 people,
how many are aged under 16?
how many are aged under 16?
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"For hver 100 mennesker,
hvor mange er under 16 år?"
hvor mange er under 16 år?"
09:04
Now, I don't know Exeter very well
at all, so I had a guess at this,
at all, so I had a guess at this,
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Nu kender jeg ikke Exeter ret godt,
så jeg gættede,
så jeg gættede,
09:08
but it gives you an idea
of how this quiz works.
of how this quiz works.
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men det giver en idé om,
hvordan denne quiz fungerer.
hvordan denne quiz fungerer.
09:10
You drag the slider
to highlight your icons,
to highlight your icons,
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Man trækker skyderen
for at fremhæve ikonerne,
for at fremhæve ikonerne,
09:14
and then just click "Submit" to answer,
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og så bare klikke på "Send" for at svare,
09:16
and we animate away the difference
between your answer and reality.
between your answer and reality.
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og vi animerer forskellen mellem
dit svar og virkeligheden.
dit svar og virkeligheden.
09:20
And it turns out, I was a pretty
terrible guess: five.
terrible guess: five.
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4075
Og det viste sig,
at jeg havde et ret forfærdeligt gæt: fem.
at jeg havde et ret forfærdeligt gæt: fem.
09:25
How about the next question?
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1424
Hvad med det næste spørgsmål?
09:26
This is asking about
what the average age is,
what the average age is,
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2156
Det spørger
hvad den gennemsnitlige alder er,
hvad den gennemsnitlige alder er,
09:28
so the age at which half
the population are younger
the population are younger
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2445
den alder, hvor halvdelen
af befolkningen er yngre
af befolkningen er yngre
09:31
and half the population are older.
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1674
og halvdelen er ældre.
09:32
And I thought 35 -- that sounds
middle-aged to me.
middle-aged to me.
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Og jeg troede 35,
det lød midaldrende for mig.
det lød midaldrende for mig.
09:36
(Laughter)
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(Latter)
09:40
Actually, in Exeter,
it's incredibly young,
it's incredibly young,
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2106
Det er utroligt ungt i Exeter.
09:42
and I had underestimated the impact
of the university in this area.
of the university in this area.
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4538
Jeg havde undervurderet virkningen
af universitetet her i området.
af universitetet her i området.
09:46
The questions get harder
as you go through.
as you go through.
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2031
Spørgsmålene bliver sværere efterhånden.
09:48
So this one's now asking
about homeownership:
about homeownership:
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2383
Denne spørger om eget hus:
09:51
For every 100 households, how many
are owned with a mortgage or loan?
are owned with a mortgage or loan?
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3699
"For hver 100 husstande,
hvor mange har et banklån?"
hvor mange har et banklån?"
09:55
And I hedged my bets here,
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1280
Jeg afdækkede
mine gæt her,
mine gæt her,
09:56
because I didn't want to be
more than 50 out on the answer.
more than 50 out on the answer.
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3098
for jeg ikke ønskede,
at have flere end 50 forkert.
at have flere end 50 forkert.
10:00
(Laughter)
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2020
(Latter)
10:02
And actually, these get harder,
these questions,
these questions,
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Disse spørgsmål bliver sværere og sværere,
10:04
because when you're in an area,
when you're in a community,
when you're in a community,
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for når du bor i et område,
når du bor i et samfund,
når du bor i et samfund,
10:07
things like age -- there are clues
to whether a population is old or young.
to whether a population is old or young.
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er der fingerpeg om,
hvorvidt befolkningen er gammel eller ung.
hvorvidt befolkningen er gammel eller ung.
10:12
Just by looking around
the area, you can see it.
the area, you can see it.
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2345
Bare ved at kigge rundt i området,
kan man se det.
kan man se det.
10:15
Something like homeownership
is much more difficult to see,
is much more difficult to see,
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3391
Noget som det at eje hus
er langt vanskeligere at se,
er langt vanskeligere at se,
10:18
so we revert to our own heuristics,
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2608
så vi vender tilbage til
vore egen heuristik,
vore egen heuristik,
10:21
our own biases about how many people
we think own their own homes.
we think own their own homes.
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4451
vore egne fordomme om, hvor mange vi tror
ejer deres eget hjem.
ejer deres eget hjem.
10:25
Now the truth is,
when we published this quiz,
when we published this quiz,
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Nu er sandheden den,
at da vi offentliggjorde denne quiz,
at da vi offentliggjorde denne quiz,
10:29
the census data that it's based on
was already a few years old.
was already a few years old.
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3536
var de data, som det er baseret på,
allerede et par år gamle.
allerede et par år gamle.
10:32
We've had online applications
that allow you to put in a post code
that allow you to put in a post code
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Vi har haft online-applikationer,
der tillader en at skrive et postnummer
der tillader en at skrive et postnummer
10:36
and get statistics back for years.
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2094
og få statistik fra årevis tilbage.
10:38
So in some senses,
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1189
Så på en måde,
10:39
this was all a little bit old
and not necessarily new.
and not necessarily new.
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3549
var dette altsammen lidt gammelt
og ikke nødvendigvis nyt.
og ikke nødvendigvis nyt.
10:43
But I was interested to see
what reaction we might get
what reaction we might get
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3639
Men jeg var interesseret i at se,
hvilken reaktion man kan få
hvilken reaktion man kan få
10:47
by game-ifying the data
in the way that we have,
in the way that we have,
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2717
ved at gamificere det
10:49
by using animation
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ved hjælp af animation
10:51
and playing on the fact
that people have their own preconceptions.
that people have their own preconceptions.
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og lege med det faktum,
at folk har deres egne fordomme.
at folk har deres egne fordomme.
10:55
It turns out, the reaction was, um ...
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3583
Det viste sig, at reaktionen
11:00
was more than I could have hoped for.
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1928
var mere end jeg kunne have håbet på.
11:02
It was a long-held ambition of mine
to bring down a statistics website
to bring down a statistics website
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3381
Det var en af mine ambitioner at bringe
en statistik-hjemmeside i knæ
en statistik-hjemmeside i knæ
11:05
due to public demand.
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1408
grundet offentlig efterspørgsel.
11:07
(Laughter)
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1800
(Latter)
11:08
This URL contains the words
"statistics," "gov" and "UK,"
"statistics," "gov" and "UK,"
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3464
Denne URL indeholder ordene
"statistik", "gov" og "UK",
"statistik", "gov" og "UK",
11:12
which are three of people's least
favorite words in a URL.
favorite words in a URL.
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3242
som er tre af folks mindst
foretrukne ord i en URL.
foretrukne ord i en URL.
11:15
And the amazing thing about this
was that the website came down
was that the website came down
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3985
Og det fantastiske ved dette var,
at hjemmesiden gik i knæ
at hjemmesiden gik i knæ
11:19
at quarter to 10 at night,
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2093
kvarter i 10 om aftenen,
11:21
because people were actually
engaging with this data
engaging with this data
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3211
fordi folk faktisk legede med disse data
11:25
of their own free will,
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1539
af egen fri vilje,
11:26
using their own personal time.
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2035
og i deres egen tid.
11:28
I was very interested to see
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Jeg fandt det meget interessant,
11:31
that we got something like
a quarter of a million people
a quarter of a million people
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679189
3713
at vi fik noget i retning af
en kvart million mennesker,
en kvart million mennesker,
11:34
playing the quiz within the space
of 48 hours of launching it.
of 48 hours of launching it.
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der spillede quizzen gennem 48 timer
efter den blev lanceret.
efter den blev lanceret.
11:38
And it sparked an enormous discussion
online, on social media,
online, on social media,
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Og det udløste en enorm diskussion online,
på sociale medier,
på sociale medier,
11:42
which was largely dominated
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2037
som i vid udstrækning var domineret
11:44
by people having fun
with their misconceptions,
with their misconceptions,
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3993
af folk, der har det sjovt
med deres misforståelser,
med deres misforståelser,
11:48
which is something that
I couldn't have hoped for any better,
I couldn't have hoped for any better,
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3059
hvilket er noget,
jeg ikke har kunnet håbe på noget bedre
jeg ikke har kunnet håbe på noget bedre
11:51
in some respects.
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1160
på en måde.
11:52
I also liked the fact that people started
sending it to politicians.
sending it to politicians.
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3226
Jeg kunne godt lide, at folk begyndte
at sende det til politikerne.
at sende det til politikerne.
11:55
How well do you know the area
you claim to represent?
you claim to represent?
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2589
Hvor godt kender du området,
du hævder at repræsentere?
du hævder at repræsentere?
11:58
(Laughter)
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1162
(Latter)
11:59
And then just to finish,
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1560
Og så bare til afslutning,
12:01
going back to the two kinds of people,
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2330
lad os gå tilbage
til de to slags mennesker.
til de to slags mennesker.
12:04
I thought it would be
really interesting to see
really interesting to see
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Jeg syntes det kunne være
interessant at se,
interessant at se,
12:06
how people who are good with numbers
would do on this quiz.
would do on this quiz.
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2815
hvordan mennesker,
der er gode til tal ville klare quizzen.
der er gode til tal ville klare quizzen.
12:09
The national statistician
of England and Wales, John Pullinger,
of England and Wales, John Pullinger,
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3016
Den nationale statistiker
i England og Wales, John Pullinger,
i England og Wales, John Pullinger,
12:12
you would expect he would be pretty good.
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2073
skulle man tro ville klare sig ret godt.
12:15
He got 44 for his own area.
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2449
Han fik 44 for sit eget område.
12:17
(Laughter)
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2468
(Latter)
12:20
Jeremy Paxman -- admittedly,
after a glass of wine -- 36.
after a glass of wine -- 36.
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4949
Jeremy Paxman --
ganske vist efter et glas vin -- 36.
ganske vist efter et glas vin -- 36.
12:26
Even worse.
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1461
Endnu værre.
12:27
It just shows you that the numbers
can inspire us all.
can inspire us all.
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3201
Det viser bare,
at tallene kan inspirere os alle.
at tallene kan inspirere os alle.
12:30
They can surprise us all.
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1260
De kan overraske os alle.
12:32
So very often, we talk about statistics
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2039
Ofte taler vi om statistik,
12:34
as being the science of uncertainty.
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742108
1962
som værende videnskaben om usikkerhed.
12:36
My parting thought for today is:
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1782
Mine afskedsord i dag er:
12:37
actually, statistics is the science of us.
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3035
I virkeligheden er statistik
videnskaben om os.
videnskaben om os.
12:40
And that's why we should
be fascinated by numbers.
be fascinated by numbers.
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2788
Og det er derfor,
vi bør være fascineret af tal.
vi bør være fascineret af tal.
12:43
Thank you very much.
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Mange tak.
12:44
(Applause)
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(Bifald)
ABOUT THE SPEAKER
Alan Smith - Data visualisation editorAlan Smith uses interactive graphics and statistics to breathe new life into how data is presented.
Why you should listen
Alan Smith is Data Visualisation Editor at the Financial Times in London. Previously he was Head of Digital Content at the UK Office for National Statistics (ONS).
With a background in cartography and digital mapping, he has spent the last decade finding ways of bringing statistics to wider audiences. In 2010, he was an inaugural recipient of the Royal Statistical Society's Award for Excellence in Official Statistics. He was appointed Office of the Order of the British Empire (OBE) in the Queen's 2011 Birthday Honours list.
Alan Smith | Speaker | TED.com