The best stats you've ever seen - Hans Rosling

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This is fascinating, thank you!

πŸ‘οΈŽ︎ 4 πŸ‘€οΈŽ︎ u/cluelessperson πŸ“…οΈŽ︎ Feb 02 2016 πŸ—«︎ replies

Summary: Asia is significantly better-off than it was fifty years ago. Africa still isn't doing so well. Standards of living look more like a bell curve than two separate groups of "rich countries" and "poor countries". Good data visualizations are important.

πŸ‘οΈŽ︎ 1 πŸ‘€οΈŽ︎ u/nounhud πŸ“…οΈŽ︎ Feb 03 2016 πŸ—«︎ replies

very entertaining, part of teaching is making it interesting. my college class is just a 3 hr power point presentation. he wonders why people fall asleep in his class.....

πŸ‘οΈŽ︎ 3 πŸ‘€οΈŽ︎ u/techno_mage πŸ“…οΈŽ︎ Feb 02 2016 πŸ—«︎ replies

When dealing with statistics you should always look for the hidden variables. Great talk!

πŸ‘οΈŽ︎ 1 πŸ‘€οΈŽ︎ u/Morigain πŸ“…οΈŽ︎ Feb 02 2016 πŸ—«︎ replies

I know this is wrong of me but I can't take him seriously after being so stringently pro-immigration and then whining that Sweden's teen sex ratio is worse than China's.

πŸ‘οΈŽ︎ 1 πŸ‘€οΈŽ︎ u/SmugAnimeFaec πŸ“…οΈŽ︎ Feb 02 2016 πŸ—«︎ replies
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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
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Channel: TED-Ed
Views: 337,397
Rating: 4.9411411 out of 5
Keywords: \Hans Rosling\, TED, TED-Ed, \TED, Ed\, TEDEducation, data
Id: usdJgEwMinM
Channel Id: undefined
Length: 19min 53sec (1193 seconds)
Published: Sat Jul 13 2013
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