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