[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

[音楽] 10 年前、私はスウェーデンの学部生に世界開発を教えるという任務を引き受けました。それはアフリカの機関と約 20 年をかけて飢餓の研究に従事した後でした

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

アフリカでの経験から、ある程度世界のことがわかっているだろうと期待されていました。そこでカロリンスカ研究所の医学部で「グローバルヘルス」という学部コースを始めましたが

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

その機会を得ると少し緊張します。スウェーデンの大学システムで最高成績を収めた学生たちがやってくると思っていました。だからもしかすると

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

彼らが来たときに事前テストを行い、そこから多くのことを学んだ質問の一つがこれです

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

5 つの国ペアの中で、どの国が最も乳児死亡率が高いかという問題です。各ペアで一方の国の乳児死亡率が他方の两倍になるように組み合わせてみました

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

つまり、データの不確実性よりもはるかに大きな差があるということです。ここではテストしませんが、答えはトルコ、ポーランド、ロシア、パキスタン、南アフリカです

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

これがスウェーデンの学生の結果です。信頼区間は非常に狭く、もちろん嬉しく思いました

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 問中平均 1.8 問正解でした。つまり国際保健の教授として私のコースにはまだ改善の余地がありました。しかしある深夜、レポートを作成しているとき

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

本当に自分の発見に気づきました。スウェーデンのトップ学生はチンパンジーより統計的に有意に世界について知らないことを示したのです。なぜならチンパンジーは

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

もしスリランカとトルコの間にバナナを二つ与えれば、半分の場合で正解するからです。しかし学生たちはそこまでは達していません。私にとっての問題は無知ではなく先入観でした

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

またカロリンスカ研究所の教授たちについても不公平で倫理的に問題のある調査を行いました。ノーベル生理学・医学賞を授与する彼らもチンパンジーと同じレベルでした

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

そこで私は、世界のデータや実際に起きていること、特に乳幼児の健康について、もっと伝える必要があると気づきました。もちろん各国はよく認識しています

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

それでこのようなソフトウェアを作りました。ここにあるそれぞれのバブルは一国を表します。こちらが中国、こちらがインドです

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

バブルの大きさは人口規模を示し、この軸には出生率を配置しました。なぜなら学生たちが世界を見て言ったことを考えると

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

まず教科書が『タンタン』ばかりだと気づき、彼らは世界をまだ「私たち」と「彼ら」に分けていると言いました。「私たち」は西洋、「彼ら」は第三世界です

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

西洋とは何かと聞くと、長寿で家族が少ない国、第三世界とは短命で家族が多い国だと説明しました

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

だからこれを可視化しました。ここに出生率、つまり女性一人あたりの子供数を 1 から 8 人まで置きました

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 年から 1968 年にかけて全国の家族規模に関するデータは非常に良く、誤差範囲も狭いです

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

次に出生時平均余命を配置しました。30 歳から約 70 歳までです。1962 年当時、工業化された国々は小さな家族で長生きしていました

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

そして発展途上国は大きな家族を持ち、相対的に短命でした。では 1962 年以来何が起こったでしょうか?変化を見たいですね

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

まだ二種類の国があるのか、それとも発展途上国は家族が減り、ここで暮らすようになったのか、あるいは寿命が延びて上に移動したのか見てみましょう。世界を一時停止します

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

これはすべて国連の統計データです。はい、中国が見えますね。より良い健康へと移動し改善されています

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

緑色のラテンアメリカ諸国は小さな家族へと向かっています。黄色いアラブ諸国は家族が増えていますが生きてはいません

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

アフリカ諸国は下の緑色で、まだここに留まっています。インドネシアは急速に進んでいます。80 年代にはバングラデシュがアフリカ諸国の中にありましたが

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

今はバングラデシュが奇跡を起こしました。80 年代にイマームたちが家族計画を推進し、あの隅へと移動しました。90 年代には

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

アフリカ諸国や世界の他の地域で平均寿命を著しく低下させる恐ろしい HIV 流行が、長寿で家族規模の小さい領域へと移動し、全く新しい世界が生まれます [拍手]

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

アメリカ合衆国とベトナムを直接比較してみましょう。1964 年、アメリカは小家族で長寿でした。一方ベトナムは大家族で短命でした。

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

これが起こったことです。戦争中のデータを見ると、多くの死者が出たにもかかわらず、年末には平均寿命が改善していました。

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

ベトナムで家族計画が始まり、小家族へ移行すると、アメリカは家族規模を維持したままより長寿へと向かいました。

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 年代に入り、ベトナムは共産主義計画を捨て市場経済へ移行しました。社会生活においてもさらに急速に変化し、今日ではベトナムも同じ期待寿命と家族規模を持っています。

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