[Music] 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 institutions 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 that so I got the confidence interval which was 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 the 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

obviously 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 and

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 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 1 2 3 4 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 China they're moving them against better health they are improving there or

the green latin-american countries they are moving towards smaller families your yellow ones here or 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 Imams 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 world moves up into the corner where we have long lives and

small family and we have a completely new world [Applause] 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 a 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 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

the 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% 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 these these where are the different countries I can show you Africa this is

Africa 10% of world population most impoverished 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 seen that wild populations increase there are hundreds of millions in Asia are 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 products and I take the regions down here the size of the bubble distill 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 their child 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 this

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 help 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 more reaches up there now reaches was the first country to get away with trade barriers and they could sell

those 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 how are

they 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 methods 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 merge 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 thank you but 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 thanks your ping came and 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 for 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 in spite 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 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 Uganda's are 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

there should be in Africa everything in this world exists in Africa and 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 webpages 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 scary 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 on the 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 secondly 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 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 the 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 fall of this over the year as I would like you to be able to do with all the publicly funded data

thank you very much what if great ideas weren't cherished what if they carried no importance or held no value there is a place where artistic vision is protected where inspired design

ideas live on to become ultimate driving machines you

The best stats you've ever seen | Hans Rosling

[Music] but ten years ago I took on the task to teach global development to Swedish undergraduate本科生 students that was after having spent about 20 years together with African institutions studying hunger

[음악] 10 년 전, 저는 스웨덴 학부생들에게 세계 개발을 가르치는 임무를 맡았습니다. 아프리카 기관들과 약 20 년 동안 기아를 연구한 후였죠.

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

아프리카에서 일했으니 세계에 대해 어느 정도는 알고 있을 것이라고 기대받았죠. 그래서 칼로린스카 의과대학에서 '글로벌 헬스'라는 학부 과정을 시작했습니다만

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

그런 기회를 얻으면 조금 긴장합니다. 스웨덴 대학 시스템에서 최고 성적을 받은 학생들이 온다고 생각했거든요. 그래서 어쩌면

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

그들이 도착했을 때 사전 테스트를 했고, 그중 많은 것을 배운 질문 하나가 바로 이것입니다.

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

이 다섯 쌍의 국가 중 어느 나라가 가장 높은 영아 사망률을 가지고 있는지 묻는 문제였습니다. 각 쌍에서 한 나라의 영아 사망률이 다른 나라의 두 배가 되도록 짝지었습니다.

this means that it's much bigger the difference than the uncertainty不确定性 of the data I won't put you to test here but it's Turkey which is high as there Poland Russia Pakistan

즉 데이터의 불확실성보다 훨씬 큰 차이입니다. 여기서는 테스트하지 않겠지만 정답은 터키, 폴란드, 러시아, 파키스탄, 남아프리카입니다.

and South Africa and these were the results of the Swedish students I did that so I got the confidence interval which was pretty narrow and I got happy of course at

이것이 스웨덴 학생들의 결과입니다. 신뢰 구간이 매우 좁았고, 물론 기뻤습니다.

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

5 문 중 평균 1.8 문 정답이었습니다. 즉 국제보건 교수로서 제 강의에는 여전히 개선의 여지가 있었습니다. 그런데 어느 깊은 밤, 보고서를 작성하면서

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

진짜 내 발견을 깨달았습니다. 스웨덴 최상위 학생들이 침팬지보다 통계적으로 유의하게 세계에 대해 덜 안다는 것을 보여준 것입니다. 왜냐하면 침팬지는

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

스리랑카와 터키 사이에 바나나 두 개를 준다면 절반의 경우 정답할 테니까요. 하지만 학생들은 그 수준에 미치지 못했습니다. 저에게 문제는 무지가 아니라 선입견이었습니다.

not ignorant it was preconceived ideas I did also an unfair unethical不道德的 study of the professors of the Karolinska Institute that hands out the Nobel Prize in medicine and they are on

또 칼로린스카 연구소 교수들에 대해서도 불공정하고 윤리적으로 문제가 있는 조사를 했습니다. 노벨 의학상을 수여하는 그들이 침팬지와 같은 수준이었기 때문입니다.

par with the 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

그래서 저는 세계의 데이터와 실제로 일어나고 있는 일, 특히 영유아 건강에 대해 더 전달해야 한다는 것을 깨달았습니다. 물론 각국은 잘 인식하고 있습니다.

obviously 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 and

그래서 이런 소프트웨어를 만들었습니다. 여기에 있는 각각의 버블은 한 나라를 나타냅니다. 여기가 중국이고, 여기가 인도입니다.

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

버블 크기는 인구 규모를 나타내고, 이 축에는 출산율을 배치했습니다. 학생들이 세상을 보며 말한 것을 고려할 때요.

and I asked them what do you really think about the world huh well I first discovered that the textbook was Tintin mainly and they said the world is still we and

먼저 교과서가 『탕탕』뿐이라고 알아차렸고, 그들은 세계를 아직 '우리'와 '그들'로 나눈다고 말했습니다. '우리'는 서구, '그들'은 제 3 세계입니다.

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

서구가 무엇인지 물으면, 장수하고 가족이 적은 나라, 제 3 세계는 단명하고 가족이 많다고 설명했습니다.

short life in large family so this is what I could display here I put fertility rate here number of children per woman 1 2 3 4 up to about eight children

그래서 이를 시각화했습니다. 여기에 출산율, 즉 여성 한 명당 자녀 수를 1 에서 8 명까지 배치했습니다.

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

1960 년부터 1968 년까지 전국의 가족 규모에 대한 데이터는 매우 양호하며 오차 범위도 좁습니다.

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

다음으로 출생 시 평균 수명을 배치했습니다. 30 세에서 약 70 세까지입니다. 1962 년 당시 산업화된 국가들은 작은 가족으로 오래 살았습니다.

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

그리고 개발도상국은 큰 가족을 가지고 상대적으로 단명했습니다. 그렇다면 1962 년 이후 무슨 일이 있었을까요? 변화를 보고 싶습니다.

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

아직 두 종류의 국가가 있는지, 아니면 개발도상국이 가족이 줄어들어 여기에 살게 되었는지, 아니면 수명이 길어져 위로 이동했는지 봅시다. 세계를 일시 정지합니다.

the world and this is all UN statistic that has been a here we go can you see that it's China they're moving them against better health they are improving there or

이는 모두 유엔 통계 데이터입니다. 네, 중국이 보입니다. 더 나은 건강으로 이동하며 개선되고 있습니다.

the green latin-american countries they are moving towards smaller families your yellow ones here or the Arabic countries and they get larger families but they no longer life but not larger families

녹색 라틴아메리카 국가들은 작은 가족으로 향하고 있습니다. 노란색 아랍 국가들은 가족이 늘었지만 생존하지는 못했습니다.

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

아프리카 국가들은 아래 녹색으로 아직 여기에 머물러 있습니다. 인도네시아는 빠르게 이동하고 있습니다. 80 년대에는 방글라데시가 아프리카 국가들 안에 있었지만

countries there but now Bangladesh it's a miracle that happens in the 80s the Imams start to promote推广 Family Planning and they move up into that corner and in 90s we have

이제는 방글라데시가 기적을 일으켰습니다. 80 년대에 이맘들이 가족 계획을 홍보하여 그 구석으로 이동했습니다. 90 년대에는

the terrible HIV epidemic that takes down the life expectancy of the African countries and all the rest of the world moves up into the corner where we have long lives and

아프리카 국가들과 세계 나머지 지역의 기대 수명을 낮추는 끔찍한 HIV 유행이 장수와 소가족 영역으로 이동하며 완전히 새로운 세상이 됩니다 [박수]

small family and we have a completely new world [Applause] let me make a comparison directly between United States of America and Vietnam 1964 America had small families and long life Vietnam

미국과 베트남을 직접 비교해 보겠습니다. 1964 년 미국은 소가족에 장수였습니다. 반면 베트남은 대가족에 단명이었습니다.

had large families and short lives and this is what happens the data during the war indicate表明 that even with all the death there was an improvement of life expectancy by the

그것이 일어난 일입니다. 전쟁 중 데이터를 보면 많은 사망자가 있었음에도 불구하고 연말에는 기대 수명이 개선되었습니다.

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 a longer life keeping family size and

베트남에서 가족 계획이 시작되어 소가족으로 전환하자, 미국은 가족 규모를 유지하면서 더 긴 수명으로 나아갔습니다.

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

80 년대에 들어 베트남은 공산주의 계획을 버리고 시장 경제로 전환했습니다. 사회 생활에서도 더욱 빠르게 변화하여 오늘날 베트남도 같은 기대 수명과 가족 규모를 가지고 있습니다.

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