The best stats youve ever seen Hans Rosling

but ten years ago I took on the task to

teach global development to Swedish

undergraduate students that was after

having spent about 20 years together

with African institution studying hunger

in Africa so I was sort of expected to

know a little about the world and I

started in our medical university

Karolinska Institute an undergraduate

course called global health but when you

get that opportunity you get a little

nervous I thought these students coming

to us actually have the highest grade

you can get in Swedish college system so

I thought maybe they know everything I’m

going to teach them about so I did a

pretest when they came and one of the

question from which I learned a lot was

this one which country has the highest

child mortality of these five pairs and

I put them together so that in each pair

of country one has twice the child

mortality of the other and this means

that it’s much bigger the difference

than the uncertainty of the data I won’t

put you to test here but it’s Turkey

which is high as there Poland Russia

Pakistan and South Africa and these were

the results of the Swedish students I

did it so I got the confidence interval

which is pretty narrow and I got happy

of course at one point eight right

answer out of five possible that means

that there was a place for a professor

of international health and for my

course but one life late-night when I

was compiling the report I really

realized my discovery I have shown that

Swedish top students know statistically

significantly less about the world than

the chimpanzees

because the chimpanzee would score half

right if I gave him two bananas with Sri

Lanka and Turkey they would be right

half of the cases but the students are

not there the problem for me was not

ignorant it was preconceived ideas I did

also an unfair unethical study of the

professors of the Karolinska Institute

that hands out the Nobel Prize in

medicine and they are on par with a

chimpanzee there so this is where I

realized that there was really a need to

communicate because the data or what’s

happening in the world and the child

health of every country is very well

aware so we did this software which

displays it like this every bubble here

is a country this country over here is

this is China this is India the size of

the bubble is the population and on this

axis here I put fertility rate because

my students what they said when they

looked upon the world and I asked them

what do you really think about the world

huh well I first discovered that the

textbook was Tintin mainly and and they

said the world is still we and them and

we is Western world and them is third

world and what do you mean with Western

world I said well that’s long life in

small family and third world is short

life in large family so this is what I

could display here I put fertility rate

here number of children per woman one

two three four up to about eight

children per woman we have very good

data since 1960 to 1968

on the size of families in all countries

the error margin is narrow here I put

life expectancy at birth from 30 years

in some countries up to about 70 years

and 1962 that was really a group of

countries here that was industrialized

countries and they had small families

and long lives and these were the

developing countries they had large

families and they had relatively short

lives now what has happened since 1962

we want to see the change or the

students right it’s still two types of

countries or have these developing

countries got smaller families and they

live here or have they got longer lives

and live up there let’s see we stopped

the world and this is all UN statistic

that has been a

here we go can you see that it’s shiner

they’re moving up against better health

are improving their or the green

latin-american countries they are moving

towards smaller families your yellow

ones here are the Arabic countries and

they get larger families but they no

longer life but not larger families the

Africans are the green down here they

still remain here this is India

Indonesia is moving on pretty fast and

in the 80s here you have Bangladesh

still among the African countries there

but now Bangladesh it’s a miracle that

happens in the 80s the moms start to

promote Family Planning and they move up

into that corner and in 90s we have the

terrible HIV epidemic that takes down

the life expectancy of the African

countries and all the rest of the mall

moves up into the corner where we have

long lives and small family and we have

a completely new world

let me make a comparison directly

between United States of America and

Vietnam 1964 America had small families

and long life Vietnam had large families

and short lives and this is what happens

the data during the war indicate that

even with all the death there was an

improvement of life expectancy by the

end of the year the Family Planning

started in Vietnam and they went for

smaller families and the United States

up there is getting for longer life

keeping family size and in the 80s now

they give up communist planning and they

go for market economy and it moves

faster even in social life and today we

have in Vietnam the same life expectancy

and the same family size here in Vietnam

19 2003 as in the United States 1974 by

the end of the war I think we all if we

don’t look in the data we underestimate

the tremendous change in Asia which was

in social change before we saw the

economical change so let’s move over to

another way here in which we could

display that distribution in the world

of the income this is the world

distribution of income of people $1 $10

or $100 per day there’s no gap between

rich and poor any longer this is a myth

there’s a little hump here but there are

people all the way and if we look where

the income ends up the income this is

100 percent of world’s annual income and

the rich is 20%

they take out of that about 74 percent

and the poor is 20 percent they take

about 2% and this shows that the concept

developing countries is extremely

doubtful we sort of think about aid like

these people here giving aid to these

people here but in the middle we have

most a world population and they have

now 24 percent of the income we heard it

in other forms and who are who are

released these where are the different

countries I can show you Africa

this is Africa 10% of world population

most in poverty

this is oacd the rich country the

country club of the UN and they are over

here on this side and quite an overlap

between Africa and oacd and this is

Latin America it has everything on this

earth from the poorest to the richest in

Latin America and on top of that we can

put East Europe we can put East Asia and

we could South Asia and how did it look

like if we go back in time to about 1970

then there was more of a hump and we

have most who lived in absolute poverty

were Asians the problem in the world was

the poverty in Asia and if I now let the

world move forward you will seem that

wild population increase there are

hundreds of millions in Asia getting out

of poverty and some others get into

poverty and this is the pattern we have

today and the best projection from the

World Bank is that this will happen and

we will not have a divided world we have

most people in the middle of course it’s

a logarithmic scale here but our concept

of economy is growth with percent we

look upon it as a possibility of percent

increase if I change this and I take GDP

per capita instead of family income and

I turn these individual data into

regional data of gross domestic product

and I take the regions down here the

size of the bubble is still the

population and you have the OECD there

and you have sub-saharan Africa there

and we take off the Arab states they’re

coming both from Africa and from Asia

and we put them separately and we can

expand this axis and I can give it a new

dimension here by adding the social

values they shall survival now I have

money on that axis and I have the

possibility of children to survive there

in some countries ninety-nine point

seven percent of children survive to

five years of age others only seventy

and here it seems that Z is a gap

between oacd Latin America East Europe

East Asia Arab States South Asia and

sub-saharan Africa the linearity is very

strong between child survival

and money but let me split sub-saharan

Africa health is there and better health

is up there I can go here and I can

split sub-saharan Africa into its

countries and when it bursts the size of

East country bubble it’s the size of the

population Sierra Leone the down there

mo reaches up there now reaches was the

first country to get away with trade

barriers and they could sell by sugar

they could sell their textiles on equal

terms as the people in Europe and North

America there’s a huge difference

between Africa and Ghana is here in the

middle in Sierra Leone a humanitarian

aid here in Uganda development aid here

time to invest there you can go for

holiday it’s a tremendous variation

within Africa which we very often make

that it’s equal everything I can split

South Asia here India’s the big bubble

in the middle but huge difference

between Afghanistan and Sri Lanka and I

can speed Arab states holiday same

climate same culture same religion huge

difference even between neighbors Yemen

Civil War United Arab Emirates money

which was quite equally and well used

not as the mythos and that includes all

the children of the foreign workers who

are in the country data is often better

than you think

many people say data is bad there is an

uncertainty margin but we can see the

difference here Cambodia Singapore the

differences are much bigger than the

weakness of the data East Europe Soviet

economy for a long time but they come

out of the ten years very very

differently and there is Latin America

today we don’t have to go to Cuba to

find a healthy country in Latin America

Chile will have a lower child mortality

than Cuba within some few years from now

and here we have high-income countries

in OECD and we get the whole pattern

here of the world which is more or less

like like this and if we look at it how

it looks the world in 1960 it starts to

move 1960 this is mouths a tomb he

brought health to China and then he died

and then things your pink a man

brought money to China and brought them

into the mainstream again and we have

seen how countries move in different

directions like this so it’s sort of

sort of difficult to get an example

country which shows the pattern of the

world but I would like to bring you back

to about here at 1960 and I would like

to compare South Korea which is this one

with with Brazil which is this one the

label went away from me here and I would

like to compare Uganda which is there

and I can run it forward like this and

you can see how South Korea is making a

very very fast advancement

whereas Brazil is much slower and if we

move back again here and we put on

trails on them like this you can see

again that the speed of development is

very very different and the countries

are moving more or less in the same rate

as money and health but it seems you can

move much faster if you’re healthy first

than if you are wealthy first and to

show that you can put on the way of

united arab emirate they came from here

a mineral country they catch all the oil

they got all the money but health cannot

be bought at the supermarket you have to

invest in health you have to get kids

into schooling you have to Train health

staff you have to educate the population

and sheikh zayed did that in a fairly

good way and the inspite of falling oil

prices he brought this country up here

so we got a much more mainstream

appearance of the world where all

countries tend to use their money better

than they used in the past now

this is more or less if you look at if

you look at the average data of the

countries they are like this now that’s

dangerous to use average data because

there’s such a lot of difference within

countries so if I go and look here we

can see that

Uganda that today is where South Korea

was 1960 if I split Uganda there’s quite

a difference within Uganda these are the

quintiles of Uganda the richest 20% of

Ugandan czar there the poorest are down

there if I split South Africa it’s like

this and if I go down and look at

Nigeria where there was such a terrible

famine lost Lee it’s like this the 20%

poorest of Nigeria is out here and the

20% richest of South Africa is there and

yet we tend to discuss on what solutions

they should be in Africa everything in

this world exists in Africa

you can’t discuss universal access to

HIV for that quintile up here with the

same strategy as down here the

improvement of the world must be highly

contextualized and it’s not relevant to

have it on regional level we must be

much more detailed we find that students

get very excited when they can use this

and even more policymakers and the

corporate sectors would like to see see

how the world is changing now why

doesn’t this take place why are we not

using the data we have we have data in

the United Nation in the National

Statistical agencies and in universities

another non-governmental organization

because the data is hidden down in the

databases and the public is there and

the internet is there but we have still

not used it effectively all that

information was so changing in the world

does not include publicly funded

statistics there are some web pages like

this you know but they take some

nourishment down from the databases but

people put prices on them stupid

passwords and boring statistics and this

won’t work

so what is needed we have the databases

it’s not a new database you need we have

wonderful design tools and more and more

I added up here so we started a

non-profit venture which we called

linking data to design we call it

Gapminder from London Underground where

they warn you mind the gap so we thought

gap mind was appropriate and we started

to write software which could link the

data like this and it wasn’t that

difficult

it took some person years and we have

produced animations you can take a data

set and put it there we are liberating

you and data some few UN organizations

some countries accept that their

databases can go out on the world but

what we really need is of course a

search function a search function where

we can copy the data up to a searchable

format and get it out in the world and

what do we hear when we go around I’ve

done anthropology on the main

statistical units everyone says it’s

impossible this can’t be done our

information is so peculiar in detail so

that cannot be searched as other can be

searched we cannot give the data free to

the students free to the entrepreneurs

of the world but this is what we would

like to see isn’t it the publicly funded

data is down here and we would like

flowers to grow out on the net and one

of the crucial point is to make them

searchable and then people can use the

different design tool to animate it

there and I have a pretty good news for

you I have a good news that the present

new head of UN statistic he doesn’t say

it’s impossible he only says we can’t do

it and that’s a quite clever guy

so we can see a lot happening in data in

the coming years we will be able to look

at income distributions in completely

new ways this is the income distribution

of China 1970 this is the income

distribution of the United States 1970

almost no overlap almost no overlap and

what has happened what has happened is

this the China is growing it’s not so

equal any longer and it’s appearing here

overlooking the United States almost

like a ghost isn’t it it’s pretty scared

but I think it’s very important to have

have all this information we need we

need really to see it and instead of

looking at this I would like to end up

by showing the Internet users per 1000

and this software we access about 500

variables from all the countries quite

easily it takes some time to change for

this but only accesses you can quite

easily get any variable you would like

to have and the thing would be to get up

the database is free to get them

searchable and with a second click to

get them into the graphic formats where

you can instantly understand them now

the statisticians doesn’t like it

because they say that this will not this

will not show the reality we have to

have statistical analytical methods but

this is hypothesis-generating

I end now with a world where the

internet are coming the number of

Internet users are going up like this

this is the GDP per capita and it’s a

new technology coming in but in

amazingly how well it fits to the

economy of the countries that’s why the

$100 computer will be so important but

it’s a nice tenders it’s as if the world

is flattening off isn’t it these

countries are lifting more than the

economy and will be very interesting to

follow this over the year as I would

like you to be able to do

with all the publicly funded data thank

you very much