[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

[音乐] 但十年前,我接手了一项任务:向瑞典本科生讲授全球发展课程。那是在我与非洲机构合作研究饥饿问题约二十年后发生的。

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

在非洲,所以我被期望对世界有些了解,于是我在卡罗林斯卡医学院开设了一门名为“全球健康”的本科课程,但是……

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

当你获得这样的机会时,你会感到有点紧张。我想这些来到我们这里的学生,在瑞典的大学体系中成绩都是顶尖的,所以我想也许……

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

他们可能知道我要教给他们的一切。于是我做了一个预测试,其中有一个问题让我学到了很多:这五组国家中,哪一组的儿童死亡率最高?

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

我把它们配对,使得每对国家中,一国的儿童死亡率是另一国的两倍。

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

这意味着差异之大远超数据的不确定性。我不打算在这里考你们,但答案是土耳其,其死亡率很高,其次是波兰、俄罗斯、巴基斯坦和南非。

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

这是瑞典学生的结果。我计算出了置信区间,范围相当窄,当然我也很高兴。

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

平均每人答对 1.8 题(共 5 题),这意味着国际健康教授职位和我的课程确实还有存在的空间。但有一天深夜,当我……

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

正在整理报告时,我真的意识到了我的发现:我已证明,瑞典顶尖学生关于世界的知识在统计上显著少于黑猩猩,因为如果给黑猩猩两个香蕉作为奖励,让它从斯里兰卡和土耳其中选一个,它也能答对一半的情况。

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

但学生们并没有达到那个水平。对我来说,问题不在于无知,而在于先入为主的观念。

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

我还进行了一项不公平且不道德的研究,对象是颁发诺贝尔医学奖的卡罗林斯卡研究所的教授们,他们的表现与黑猩猩不相上下。

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

因此我意识到,确实需要加强沟通,因为世界上的数据和儿童健康状况显然各国都了如指掌。

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

所以我们开发了这款软件,显示效果如下:这里的每个气泡代表一个国家,这个国家是中国。

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

这个是印度。气泡的大小代表人口数量,而在横轴上,我放置的是生育率,因为我的学生在观察世界时曾这样说过。

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

我问他们:“你对这个世界到底是怎么看的?”嗯,我首先发现教科书主要是《丁丁历险记》,他们说世界仍然是‘我们’和‘他们’。

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

'我们'指的是西方世界,'他们'指的是第三世界。我说什么是西方世界呢?那就是长寿且家庭规模小;而第三世界则是短寿且家庭规模大。

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

这就是我能展示的内容:我将生育率放在这里,即每位女性的子女数量,从 1 到 2、3、4,直到大约 8 个。

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

自 1960 年至 1968 年,我们在所有国家的家庭规模方面拥有非常可靠的数据,误差范围很小。接着我放入了出生时的预期寿命。

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

从某些国家的 30 岁到大约 70 岁。1962 年,有一群国家位于此处,它们是工业化国家,家庭规模小,寿命长。

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

而那些发展中国家则家庭规模大,寿命相对较短。那么自 1962 年以来发生了什么?我们要看看变化,或者验证学生的观点是否正确。

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

现在是否仍有两类国家?还是说这些发展中国家的家庭变小了,人们活得更长了,移到了上方?让我们看看。

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

世界停止了,这些都是联合国统计数据。看,是中国,它们正朝着更好的健康方向移动,情况正在改善。

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

绿色的拉丁美洲国家正朝着家庭规模变小的方向发展;黄色的阿拉伯国家虽然不再长寿,但家庭规模并未变大。

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

非洲国家(下方的绿色)仍然停留在此处。印度和印度尼西亚移动得很快。在 80 年代,孟加拉国仍被视为非洲国家之一。

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

但现在孟加拉国发生了奇迹。80 年代,伊玛目们开始推广计划生育,它们便移向了那个角落。到了 90 年代,我们有……

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

那场可怕的艾滋病疫情拉低了非洲国家乃至全球其余地区的预期寿命,使这些地区的数据点移向了原本代表长寿的角落。

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

小家庭与长寿共存,我们迎来了一个全新的世界。[掌声] 让我直接对比一下美国和越南:1964年的美国是小家庭、高寿命,而越南……

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

……拥有大家庭和短寿命。战争期间的数据显示,尽管死亡惨重,但到年底时预期寿命反而有所提升。

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

随后越南启动了计划生育,转向小家庭模式,而美国则继续追求更长的寿命并维持家庭规模不变。

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

到了80年代,他们放弃了计划经济,转而实行市场经济,社会生活的发展速度也加快了。如今,越南的预期寿命和家庭规模已与美国1974年的水平持平。

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