[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:03.20,0:00:10.04,Default,,0000,0000,0000,,The world we live in is awash with\Ndata that comes pouring in\Nfrom everywhere around us.
Dialogue: 0,0:00:10.04,0:00:14.52,Default,,0000,0000,0000,,On its own this data\Nis just noise and confusion.
Dialogue: 0,0:00:14.52,0:00:22.52,Default,,0000,0000,0000,,To make sense of data, to find the\Nmeaning in it, we need the powerful\Nbranch of science - statistics.
Dialogue: 0,0:00:22.52,0:00:26.04,Default,,0000,0000,0000,,Believe me there's nothing\Nboring about statistics.
Dialogue: 0,0:00:26.04,0:00:29.40,Default,,0000,0000,0000,,Especially not today\Nwhen we can make the data sing.
Dialogue: 0,0:00:29.40,0:00:33.40,Default,,0000,0000,0000,,With statistics we can\Nreally make sense of the world.
Dialogue: 0,0:00:33.40,0:00:35.04,Default,,0000,0000,0000,,And there's more.
Dialogue: 0,0:00:35.04,0:00:40.44,Default,,0000,0000,0000,,With statistics, the data deluge, as\Nit's being called, is leading us
Dialogue: 0,0:00:40.44,0:00:46.24,Default,,0000,0000,0000,,to an ever greater understanding\Nof life on Earth\Nand the universe beyond.
Dialogue: 0,0:00:46.24,0:00:50.76,Default,,0000,0000,0000,,And thanks to the incredible\Npower of today's computers,
Dialogue: 0,0:00:50.76,0:00:57.04,Default,,0000,0000,0000,,it may fundamentally transform the\Nprocess of scientific discovery.
Dialogue: 0,0:00:57.04,0:01:02.56,Default,,0000,0000,0000,,I kid you not, statistics is\Nnow the sexiest subject around.
Dialogue: 0,0:01:23.00,0:01:25.60,Default,,0000,0000,0000,,Did you know that there is\None million boats in Sweden?
Dialogue: 0,0:01:25.60,0:01:27.96,Default,,0000,0000,0000,,That's one boat per nine people!
Dialogue: 0,0:01:27.96,0:01:31.08,Default,,0000,0000,0000,,It's the highest number of\Nboats per person in Europe!
Dialogue: 0,0:01:41.08,0:01:45.76,Default,,0000,0000,0000,,Being a statistician,\Nyou don't like telling\Nyour profession at dinner parties.
Dialogue: 0,0:01:45.76,0:01:48.44,Default,,0000,0000,0000,,But really,\Nstatisticians shouldn't be shy
Dialogue: 0,0:01:48.44,0:01:51.32,Default,,0000,0000,0000,,because everyone wants to\Nunderstand what's going on.
Dialogue: 0,0:01:51.32,0:01:56.48,Default,,0000,0000,0000,,And statistics gives us a\Nperspective on the world we live in
Dialogue: 0,0:01:56.48,0:01:59.32,Default,,0000,0000,0000,,that we can't get in any other way.
Dialogue: 0,0:02:03.52,0:02:09.00,Default,,0000,0000,0000,,Statistics tells us whether\Nthe things we think\Nand believe are actually true.
Dialogue: 0,0:02:19.96,0:02:25.44,Default,,0000,0000,0000,,And statistics are far more useful\Nthan we usually like to admit.
Dialogue: 0,0:02:25.44,0:02:29.60,Default,,0000,0000,0000,,In the last recession there\Nwas this famous call-in\Nto a talk radio station.
Dialogue: 0,0:02:29.60,0:02:37.28,Default,,0000,0000,0000,,The man complained, "In times like\Nthis when unemployment rates are up\Nto 13%, income has fallen by 5%,
Dialogue: 0,0:02:37.28,0:02:41.36,Default,,0000,0000,0000,,"and suicide rates are climbing, and\NI get so angry that the government
Dialogue: 0,0:02:41.36,0:02:45.52,Default,,0000,0000,0000,,"is wasting money on things like\Ncollection of statistics."
Dialogue: 0,0:02:48.24,0:02:50.36,Default,,0000,0000,0000,,I'm not officially a statistician.
Dialogue: 0,0:02:50.36,0:02:55.28,Default,,0000,0000,0000,,Strictly speaking,\Nmy field is global health.
Dialogue: 0,0:02:58.12,0:03:03.28,Default,,0000,0000,0000,,But I got really obsessed with stats\Nwhen I realised how much people
Dialogue: 0,0:03:03.28,0:03:06.24,Default,,0000,0000,0000,,in Sweden just don't know\Nabout the rest of the world.
Dialogue: 0,0:03:06.24,0:03:10.80,Default,,0000,0000,0000,,I started in our medical\Nuniversity, Karolinska Institutet,
Dialogue: 0,0:03:10.80,0:03:13.96,Default,,0000,0000,0000,,an undergraduate course\Ncalled Global Health.
Dialogue: 0,0:03:13.96,0:03:17.36,Default,,0000,0000,0000,,These students coming to us actually\Nhave the highest grade you can get
Dialogue: 0,0:03:17.36,0:03:18.84,Default,,0000,0000,0000,,in the Swedish college system,
Dialogue: 0,0:03:18.84,0:03:22.04,Default,,0000,0000,0000,,so I thought, "Maybe they know\Neverything I'm going to teach them."
Dialogue: 0,0:03:22.04,0:03:25.68,Default,,0000,0000,0000,,So I did a pre-test when they came,\Nand one of the questions
Dialogue: 0,0:03:25.68,0:03:28.16,Default,,0000,0000,0000,,from which I learned a lot\Nwas this one -
Dialogue: 0,0:03:28.16,0:03:32.36,Default,,0000,0000,0000,,which country has the highest\Nchild mortality of these five pairs?
Dialogue: 0,0:03:32.36,0:03:34.92,Default,,0000,0000,0000,,I won't put you at test here,\Nbut it is Turkey
Dialogue: 0,0:03:34.92,0:03:37.00,Default,,0000,0000,0000,,which is highest there, Poland,
Dialogue: 0,0:03:37.00,0:03:40.76,Default,,0000,0000,0000,,Russia, Pakistan, and South Africa.
Dialogue: 0,0:03:40.76,0:03:43.08,Default,,0000,0000,0000,,And these were the result of\Nthe Swedish students.
Dialogue: 0,0:03:43.08,0:03:44.76,Default,,0000,0000,0000,,A 1.8 right answer\Nout of five possible.
Dialogue: 0,0:03:44.76,0:03:49.92,Default,,0000,0000,0000,,And that means there was a place for\Na professor of International Health\Nand for my course.
Dialogue: 0,0:03:49.92,0:03:56.36,Default,,0000,0000,0000,,But one late night\Nwhen I was compiling the report,\NI really realised my discovery.
Dialogue: 0,0:03:56.36,0:04:01.16,Default,,0000,0000,0000,,I had shown that Swedish\Ntop students know statistically
Dialogue: 0,0:04:01.16,0:04:04.48,Default,,0000,0000,0000,,significantly less about\Nthe world than the chimpanzees.
Dialogue: 0,0:04:06.00,0:04:09.84,Default,,0000,0000,0000,,Because the chimpanzees\Nwould score half right.
Dialogue: 0,0:04:09.84,0:04:12.32,Default,,0000,0000,0000,,If I gave them two bananas\Nwith Sri Lanka and Turkey,
Dialogue: 0,0:04:12.32,0:04:15.60,Default,,0000,0000,0000,,they would be right\Nhalf of the cases,\Nbut the students are not there.
Dialogue: 0,0:04:15.60,0:04:20.20,Default,,0000,0000,0000,,I did also an unethical study\Nof the professors of\Nthe Karolinska Institutet,
Dialogue: 0,0:04:20.20,0:04:25.52,Default,,0000,0000,0000,,that hands out the Nobel Prize\Nfor medicine, and they are on par\Nwith the chimpanzees there.
Dialogue: 0,0:04:28.16,0:04:32.68,Default,,0000,0000,0000,,Today there's more information\Naccessible than ever before.
Dialogue: 0,0:04:32.68,0:04:35.76,Default,,0000,0000,0000,,'And I work with my team at\Nthe Gapminder Foundation
Dialogue: 0,0:04:35.76,0:04:41.60,Default,,0000,0000,0000,,'using new tools that help everyone\Nmake sense of the changing world.
Dialogue: 0,0:04:41.60,0:04:45.32,Default,,0000,0000,0000,,'We draw on the masses of data\Nthat's now freely available
Dialogue: 0,0:04:45.32,0:04:49.72,Default,,0000,0000,0000,,'from international institutions\Nlike the UN and the World Bank.
Dialogue: 0,0:04:49.72,0:04:53.64,Default,,0000,0000,0000,,'And it's become my mission to\Nshare the insights
Dialogue: 0,0:04:53.64,0:05:00.20,Default,,0000,0000,0000,,'from this data with anyone who'll\Nlisten, and to reveal how statistics\Nis nothing to be frightened of.'
Dialogue: 0,0:05:02.44,0:05:05.04,Default,,0000,0000,0000,,I'm going to provide you a view of
Dialogue: 0,0:05:05.04,0:05:09.00,Default,,0000,0000,0000,,the global health situation\Nacross mankind.
Dialogue: 0,0:05:09.00,0:05:14.16,Default,,0000,0000,0000,,And I'm going to do that in\Nhopefully an enjoyable way,\Nso relax.
Dialogue: 0,0:05:14.16,0:05:17.12,Default,,0000,0000,0000,,So we did this software\Nwhich displays it like this.
Dialogue: 0,0:05:17.12,0:05:19.32,Default,,0000,0000,0000,,Every bubble here is a country -
Dialogue: 0,0:05:19.32,0:05:21.32,Default,,0000,0000,0000,,this is China, this is India.
Dialogue: 0,0:05:21.32,0:05:23.56,Default,,0000,0000,0000,,The size of the bubble\Nis the population.
Dialogue: 0,0:05:23.56,0:05:27.60,Default,,0000,0000,0000,,I'm going to stage a race between\Nthis sort of yellowish Ford here
Dialogue: 0,0:05:27.60,0:05:32.76,Default,,0000,0000,0000,,and the red Toyota down there\Nand the brownish Volvo.
Dialogue: 0,0:05:32.76,0:05:36.44,Default,,0000,0000,0000,,The Toyota has a very bad start\Ndown here, and United States,
Dialogue: 0,0:05:36.44,0:05:38.28,Default,,0000,0000,0000,,Ford is going off-road there,
Dialogue: 0,0:05:38.28,0:05:40.48,Default,,0000,0000,0000,,and the Volvo is doing quite fine,\Nthis is the war.
Dialogue: 0,0:05:40.48,0:05:43.68,Default,,0000,0000,0000,,The Toyota got off track, now Toyota\Nis on the healthier side of Sweden.
Dialogue: 0,0:05:43.68,0:05:46.80,Default,,0000,0000,0000,,That's about where I sold\Nthe Volvo and bought the Toyota.
Dialogue: 0,0:05:46.80,0:05:47.96,Default,,0000,0000,0000,,AUDIENCE LAUGH
Dialogue: 0,0:05:47.96,0:05:50.84,Default,,0000,0000,0000,,This is the great leap forward,\Nwhen China fell down.
Dialogue: 0,0:05:50.84,0:05:53.08,Default,,0000,0000,0000,,It was the central planning\Nby Mao Zedong.
Dialogue: 0,0:05:53.08,0:05:56.68,Default,,0000,0000,0000,,China recovered and said, "Never\Nmore stupid central planning,"
Dialogue: 0,0:05:56.68,0:05:57.80,Default,,0000,0000,0000,,but they went up here.
Dialogue: 0,0:05:57.80,0:06:02.56,Default,,0000,0000,0000,,No, there is one more inequity,\Nlook there - United States
Dialogue: 0,0:06:02.56,0:06:07.48,Default,,0000,0000,0000,,They broke my frame. Washington DC\Nis so rich over there,
Dialogue: 0,0:06:07.48,0:06:13.04,Default,,0000,0000,0000,,but they are\Nnot as healthy as Kerala in India.\NIt's quite interesting, isn't it?
Dialogue: 0,0:06:13.04,0:06:14.60,Default,,0000,0000,0000,,LAUGHTER AND APPLAUSE
Dialogue: 0,0:06:20.36,0:06:25.52,Default,,0000,0000,0000,,Welcome to the USA,\Nworld leaders in big cars
Dialogue: 0,0:06:25.52,0:06:28.48,Default,,0000,0000,0000,,and free data.
Dialogue: 0,0:06:28.48,0:06:35.88,Default,,0000,0000,0000,,There are many here who share\Nmy vision of making public data\Naccessible and useful for everyone.
Dialogue: 0,0:06:35.88,0:06:43.44,Default,,0000,0000,0000,,The city of San Francisco\Nis in the lead, opening up\Nits data on everything.
Dialogue: 0,0:06:43.44,0:06:47.48,Default,,0000,0000,0000,,Even the police department is\Nreleasing all its crime reports.
Dialogue: 0,0:06:47.48,0:06:50.84,Default,,0000,0000,0000,,This official\Ncrime data has been turned
Dialogue: 0,0:06:50.84,0:06:55.96,Default,,0000,0000,0000,,into a wonderful interactive map by\Ntwo of the city's computer whizzes.
Dialogue: 0,0:06:55.96,0:06:58.92,Default,,0000,0000,0000,,It's community statistics in action.
Dialogue: 0,0:07:09.40,0:07:13.32,Default,,0000,0000,0000,,Crimespotting is\Na map of crime reports from the\NSan Francisco Police Department
Dialogue: 0,0:07:13.32,0:07:16.12,Default,,0000,0000,0000,,showing dots on maps\Nfor citizens to be able to see
Dialogue: 0,0:07:16.12,0:07:19.32,Default,,0000,0000,0000,,patterns of crime around their\Nneighbourhoods in San Francisco.
Dialogue: 0,0:07:19.32,0:07:25.08,Default,,0000,0000,0000,,The map is not just about individual\Ncrimes but about broader patterns\Nthat show you where crime is
Dialogue: 0,0:07:25.08,0:07:27.76,Default,,0000,0000,0000,,clustered around the city, which\Nareas have high crime,
Dialogue: 0,0:07:27.76,0:07:30.32,Default,,0000,0000,0000,,and which areas have\Nrelatively low crime.
Dialogue: 0,0:07:36.84,0:07:41.44,Default,,0000,0000,0000,,We're here at the top of\NJones Street on Nob Hill...
Dialogue: 0,0:07:42.96,0:07:45.28,Default,,0000,0000,0000,,..quite a nice neighbourhood.
Dialogue: 0,0:07:45.28,0:07:49.60,Default,,0000,0000,0000,,What the crime maps show us\Nis the relationship between
Dialogue: 0,0:07:49.60,0:07:51.36,Default,,0000,0000,0000,,topography and crime.
Dialogue: 0,0:07:51.36,0:07:54.52,Default,,0000,0000,0000,,Basically the higher up the hill,\Nthe less crime there is.
Dialogue: 0,0:07:56.20,0:07:58.64,Default,,0000,0000,0000,,You cross over the border
Dialogue: 0,0:07:58.64,0:08:00.24,Default,,0000,0000,0000,,into the flats...
Dialogue: 0,0:08:02.80,0:08:09.24,Default,,0000,0000,0000,,Essentially as soon as you get\Ninto the lower lying areas of Jones\NStreet the crime just skyrockets.
Dialogue: 0,0:08:20.24,0:08:24.16,Default,,0000,0000,0000,,We're here in\Nthe uptown Tenderloin district.
Dialogue: 0,0:08:26.04,0:08:30.32,Default,,0000,0000,0000,,It's one of the oldest and densest\Nneighbourhoods in San Francisco.
Dialogue: 0,0:08:30.32,0:08:32.40,Default,,0000,0000,0000,,This is where you go to buy drugs.
Dialogue: 0,0:08:32.40,0:08:33.92,Default,,0000,0000,0000,,Right around here.
Dialogue: 0,0:08:37.20,0:08:41.64,Default,,0000,0000,0000,,We see lots of aggravated assaults,\Nlots of auto thefts.
Dialogue: 0,0:08:41.64,0:08:48.52,Default,,0000,0000,0000,,Basically a huge part of the crime\Nthat happens in the city happens\Nin this five or six block radius.
Dialogue: 0,0:08:55.64,0:08:58.92,Default,,0000,0000,0000,,If you've been hearing police sirens\Nin your neighbourhood,
Dialogue: 0,0:08:58.92,0:09:02.00,Default,,0000,0000,0000,,you can use the map to find out why.
Dialogue: 0,0:09:02.00,0:09:05.68,Default,,0000,0000,0000,,If you're out at night in\Nan unfamiliar part of town,
Dialogue: 0,0:09:05.68,0:09:09.24,Default,,0000,0000,0000,,you can check the map\Nfor streets to avoid.
Dialogue: 0,0:09:09.24,0:09:12.40,Default,,0000,0000,0000,,If a neighbour gets burgled,\Nyou can see -
Dialogue: 0,0:09:12.40,0:09:16.52,Default,,0000,0000,0000,,is it a one-off or has there been\Na spike in local crime?
Dialogue: 0,0:09:16.52,0:09:19.48,Default,,0000,0000,0000,,If you commute through a\Nneighbourhood and you're worried
Dialogue: 0,0:09:19.48,0:09:23.08,Default,,0000,0000,0000,,about its safety, the fact that we\Nhave the ability to turn off all
Dialogue: 0,0:09:23.08,0:09:25.36,Default,,0000,0000,0000,,the night-time\Nand middle-of-the-day crimes
Dialogue: 0,0:09:25.36,0:09:28.28,Default,,0000,0000,0000,,and show you just the things that are\Nhappening during the commute,
Dialogue: 0,0:09:28.28,0:09:32.88,Default,,0000,0000,0000,,it is a statistical operation.\NBut I think to people that are\Ninteracting with the thing
Dialogue: 0,0:09:32.88,0:09:38.00,Default,,0000,0000,0000,,it feels very much more like they're\Njust sort of browsing a website\Nor shopping on Amazon.
Dialogue: 0,0:09:38.00,0:09:43.52,Default,,0000,0000,0000,,They're looking at data\Nand they don't realise\Nthey're doing statistics.
Dialogue: 0,0:09:43.52,0:09:47.84,Default,,0000,0000,0000,,What's most exciting for me\Nis that public statistics
Dialogue: 0,0:09:47.84,0:09:52.64,Default,,0000,0000,0000,,is making citizens more powerful and\Nthe authorities more accountable.
Dialogue: 0,0:10:02.36,0:10:04.76,Default,,0000,0000,0000,,We have community meetings that\Nthe police attend
Dialogue: 0,0:10:04.76,0:10:08.88,Default,,0000,0000,0000,,and what citizens are\Nnow doing are bringing printouts
Dialogue: 0,0:10:08.88,0:10:12.24,Default,,0000,0000,0000,,of the maps that show where crimes\Nare taking place,
Dialogue: 0,0:10:12.24,0:10:16.12,Default,,0000,0000,0000,,and they're demanding services\Nfrom the police department
Dialogue: 0,0:10:16.12,0:10:20.52,Default,,0000,0000,0000,,and the police department is now\Nhaving to change how they police,
Dialogue: 0,0:10:20.52,0:10:22.96,Default,,0000,0000,0000,,how they provide policing services,
Dialogue: 0,0:10:22.96,0:10:27.04,Default,,0000,0000,0000,,because the data is showing\Nwhat is working and what is not.
Dialogue: 0,0:10:28.56,0:10:31.96,Default,,0000,0000,0000,,People in San Francisco\Nare also using public data
Dialogue: 0,0:10:31.96,0:10:35.80,Default,,0000,0000,0000,,to map social inequalities\Nand see how to improve society.
Dialogue: 0,0:10:35.80,0:10:39.72,Default,,0000,0000,0000,,And the possibilities are endless.
Dialogue: 0,0:10:39.72,0:10:43.16,Default,,0000,0000,0000,,I think our dream\Ngovernment data analysis project
Dialogue: 0,0:10:43.16,0:10:46.24,Default,,0000,0000,0000,,would really be focused on\Nlive information,
Dialogue: 0,0:10:46.24,0:10:51.24,Default,,0000,0000,0000,,on stuff that was being reported\Nand pushed out to the world over\Nthe internet as it was happening.
Dialogue: 0,0:10:51.24,0:10:55.04,Default,,0000,0000,0000,,You know, trash pickups,\Ntraffic accidents, buses,
Dialogue: 0,0:10:55.04,0:10:57.68,Default,,0000,0000,0000,,and I think through the kind of\Nstats-gathering power
Dialogue: 0,0:10:57.68,0:11:02.52,Default,,0000,0000,0000,,of the internet\Nit's possible to really begin\Nto see the workings of the city
Dialogue: 0,0:11:02.52,0:11:04.76,Default,,0000,0000,0000,,displayed as a unified interface.
Dialogue: 0,0:11:07.32,0:11:09.96,Default,,0000,0000,0000,,So that's where we are heading.
Dialogue: 0,0:11:09.96,0:11:14.76,Default,,0000,0000,0000,,Towards a world of free data\Nwith all the statistical\Ninsights that come from it,
Dialogue: 0,0:11:14.76,0:11:21.80,Default,,0000,0000,0000,,accessible to everyone, empowering\Nus as citizens and letting us\Nhold our rulers to account.
Dialogue: 0,0:11:21.80,0:11:26.92,Default,,0000,0000,0000,,It's a long way from\Nwhere statistics began.
Dialogue: 0,0:11:26.92,0:11:32.88,Default,,0000,0000,0000,,Statistics\Nare essential to us to monitor\Nour governments and our societies.
Dialogue: 0,0:11:32.88,0:11:36.76,Default,,0000,0000,0000,,But it was our rulers up\Nthere who started
Dialogue: 0,0:11:36.76,0:11:40.84,Default,,0000,0000,0000,,the collection of statistics in the\Nfirst place in order to monitor us!
Dialogue: 0,0:11:46.88,0:11:51.44,Default,,0000,0000,0000,,In fact the word 'statistics'\Ncomes from 'the state'.
Dialogue: 0,0:11:51.44,0:11:55.60,Default,,0000,0000,0000,,Modern statistics\Nbegan two centuries ago.
Dialogue: 0,0:11:55.60,0:11:59.08,Default,,0000,0000,0000,,Once it got going,\Nit spread and never stopped.
Dialogue: 0,0:11:59.08,0:12:01.64,Default,,0000,0000,0000,,And guess who was first!
Dialogue: 0,0:12:03.28,0:12:07.56,Default,,0000,0000,0000,,The Chinese have Confucius,\Nthe Italians have da Vinci,
Dialogue: 0,0:12:07.56,0:12:10.24,Default,,0000,0000,0000,,and the British have Shakespeare.
Dialogue: 0,0:12:10.24,0:12:12.44,Default,,0000,0000,0000,,And we have the Tabellverket -
Dialogue: 0,0:12:12.44,0:12:16.40,Default,,0000,0000,0000,,the first ever systematic\Ncollection of statistics!
Dialogue: 0,0:12:16.40,0:12:21.64,Default,,0000,0000,0000,,Since the year 1749\Nwe have collected data
Dialogue: 0,0:12:21.64,0:12:26.92,Default,,0000,0000,0000,,on every birth, marriage and death,\Nand we are proud of it!
Dialogue: 0,0:12:29.12,0:12:32.00,Default,,0000,0000,0000,,The Tabellverket recorded\Ninformation
Dialogue: 0,0:12:32.00,0:12:34.04,Default,,0000,0000,0000,,from every parish in Sweden.
Dialogue: 0,0:12:34.04,0:12:39.08,Default,,0000,0000,0000,,It was a huge quantity of data and\Nit was the first time any government
Dialogue: 0,0:12:39.08,0:12:41.80,Default,,0000,0000,0000,,could get an accurate\Npicture of its people.
Dialogue: 0,0:12:49.36,0:12:53.36,Default,,0000,0000,0000,,Sweden had been the greatest\Nmilitary power in Northern Europe,
Dialogue: 0,0:12:53.36,0:12:58.20,Default,,0000,0000,0000,,but by 1749 our star\Nwas really fading
Dialogue: 0,0:12:58.20,0:13:00.92,Default,,0000,0000,0000,,and other countries\Nwere growing stronger.
Dialogue: 0,0:13:00.92,0:13:03.60,Default,,0000,0000,0000,,At least we were a large power,
Dialogue: 0,0:13:03.60,0:13:09.96,Default,,0000,0000,0000,,thought to have 20 million people,\Nenough to rival Britain and France.
Dialogue: 0,0:13:13.40,0:13:18.16,Default,,0000,0000,0000,,But we were in for a nasty surprise.
Dialogue: 0,0:13:18.16,0:13:20.68,Default,,0000,0000,0000,,The first analysis\Nof the Tabellverket
Dialogue: 0,0:13:20.68,0:13:24.08,Default,,0000,0000,0000,,revealed that Sweden\Nonly had two million inhabitants.
Dialogue: 0,0:13:24.08,0:13:30.68,Default,,0000,0000,0000,,Sweden was not just a power\Nin decline, it also had\Na very small population.
Dialogue: 0,0:13:30.68,0:13:36.08,Default,,0000,0000,0000,,The government was horrified\Nby this finding -\Nwhat if the enemy found out?
Dialogue: 0,0:13:37.84,0:13:44.56,Default,,0000,0000,0000,,But the Tabellverket also showed\Nthat many women died in childbirth\Nand many children died young.
Dialogue: 0,0:13:44.56,0:13:48.64,Default,,0000,0000,0000,,So government took action\Nto improve the health of the people.
Dialogue: 0,0:13:48.64,0:13:52.44,Default,,0000,0000,0000,,This was the beginning\Nof modern Sweden.
Dialogue: 0,0:13:53.96,0:13:59.00,Default,,0000,0000,0000,,It took more than 50 years before\Nthe Austrians, Belgians, Danes,
Dialogue: 0,0:13:59.00,0:14:02.32,Default,,0000,0000,0000,,Dutch, French, Germans, Italians
Dialogue: 0,0:14:02.32,0:14:08.60,Default,,0000,0000,0000,,and, finally, the British,\Ncaught up with Sweden\Nin collecting and using statistics.
Dialogue: 0,0:14:24.64,0:14:29.64,Default,,0000,0000,0000,,It was called political arithmetic.\NIt was a lovely phrase\Nthat was used for statistics.
Dialogue: 0,0:14:29.64,0:14:33.16,Default,,0000,0000,0000,,Governments could have much more\Ncontrol and understanding of
Dialogue: 0,0:14:33.16,0:14:36.84,Default,,0000,0000,0000,,the society - how it was working,\Nhow it was developing
Dialogue: 0,0:14:36.84,0:14:40.24,Default,,0000,0000,0000,,and essentially\Nso they could control it better.
Dialogue: 0,0:14:43.36,0:14:47.96,Default,,0000,0000,0000,,It wasn't just governments who\Nwoke up to the power of statistics.
Dialogue: 0,0:14:47.96,0:14:54.60,Default,,0000,0000,0000,,Right across Europe, 19th\Ncentury society went mad for facts.
Dialogue: 0,0:14:54.60,0:14:57.60,Default,,0000,0000,0000,,And, despite its late start,\NBritain,
Dialogue: 0,0:14:57.60,0:15:01.40,Default,,0000,0000,0000,,with its Royal Statistical Society\Nin London,
Dialogue: 0,0:15:01.40,0:15:04.00,Default,,0000,0000,0000,,was soon a statisticians' nirvana.
Dialogue: 0,0:15:05.92,0:15:09.96,Default,,0000,0000,0000,,I love looking at old copies of\Nthe Royal Statistical Society journal
Dialogue: 0,0:15:09.96,0:15:11.76,Default,,0000,0000,0000,,because it's full of such odd stuff.
Dialogue: 0,0:15:11.76,0:15:14.84,Default,,0000,0000,0000,,There's a wonderful paper\Nfrom the 1840s
Dialogue: 0,0:15:14.84,0:15:19.20,Default,,0000,0000,0000,,which shows a map of England and\Nthe rates of bastardy in each county.
Dialogue: 0,0:15:19.20,0:15:23.56,Default,,0000,0000,0000,,So you can identify very quickly the\Nareas with high rates of bastardy.
Dialogue: 0,0:15:23.56,0:15:27.24,Default,,0000,0000,0000,,Being in East Anglia it always\Nmakes me slightly laugh that Norfolk
Dialogue: 0,0:15:27.24,0:15:30.72,Default,,0000,0000,0000,,seems to top the "bastardy league"\Nin the 1840s.
Dialogue: 0,0:15:30.72,0:15:36.80,Default,,0000,0000,0000,,One of the founders of\Nthe Royal Statistical Society
Dialogue: 0,0:15:36.80,0:15:42.12,Default,,0000,0000,0000,,was the great\NVictorian mathematician\Nand inventor Charles Babbage.
Dialogue: 0,0:15:42.12,0:15:50.12,Default,,0000,0000,0000,,In 1842 he read the latest\Npoem by an equally great Victorian,\NAlfred Tennyson.
Dialogue: 0,0:15:50.12,0:15:53.12,Default,,0000,0000,0000,,Vision of Sin contained the lines:
Dialogue: 0,0:15:53.12,0:15:55.80,Default,,0000,0000,0000,,"Fill the cup, and fill the can
Dialogue: 0,0:15:55.80,0:15:58.16,Default,,0000,0000,0000,,"Have a rouse before the morn
Dialogue: 0,0:15:58.16,0:16:03.72,Default,,0000,0000,0000,,"Every moment dies a man\NEvery moment one is born."
Dialogue: 0,0:16:03.72,0:16:07.36,Default,,0000,0000,0000,,So keen a statistician was Babbage\Nthat he could not contain himself.
Dialogue: 0,0:16:07.36,0:16:09.36,Default,,0000,0000,0000,,He dashed off a letter to Tennyson
Dialogue: 0,0:16:09.36,0:16:12.20,Default,,0000,0000,0000,,explaining that because of\Npopulation growth,
Dialogue: 0,0:16:12.20,0:16:13.64,Default,,0000,0000,0000,,the line should read,
Dialogue: 0,0:16:13.64,0:16:18.64,Default,,0000,0000,0000,,"Every moment dies a man\Nand one and a 16th is born."
Dialogue: 0,0:16:18.64,0:16:22.48,Default,,0000,0000,0000,,I may add that\Nthe exact figure is 1.067,
Dialogue: 0,0:16:22.48,0:16:27.20,Default,,0000,0000,0000,,but something must be\Nconceded to the laws of metre.
Dialogue: 0,0:16:31.84,0:16:36.64,Default,,0000,0000,0000,,In the 19th century, scholars all\Nover Europe did amazing work
Dialogue: 0,0:16:36.64,0:16:39.00,Default,,0000,0000,0000,,in measuring their societies.
Dialogue: 0,0:16:39.00,0:16:42.60,Default,,0000,0000,0000,,They were hoovering up\Ndata on almost everything.
Dialogue: 0,0:16:42.60,0:16:46.04,Default,,0000,0000,0000,,But numbers alone\Ndon't tell you anything.
Dialogue: 0,0:16:46.04,0:16:51.32,Default,,0000,0000,0000,,You have to analyse them,\Nand that's what makes statistics.
Dialogue: 0,0:16:55.76,0:16:59.20,Default,,0000,0000,0000,,When the first statisticians\Nbegan to get to grips with
Dialogue: 0,0:16:59.20,0:17:00.40,Default,,0000,0000,0000,,analysing their data
Dialogue: 0,0:17:00.40,0:17:05.76,Default,,0000,0000,0000,,they seized upon the average, and\Nthey took the average of everything.
Dialogue: 0,0:17:09.72,0:17:13.76,Default,,0000,0000,0000,,What's so great\Nabout an average is that
Dialogue: 0,0:17:13.76,0:17:18.64,Default,,0000,0000,0000,,you can take a whole mass of data\Nand reduce it to a single number.
Dialogue: 0,0:17:21.88,0:17:26.12,Default,,0000,0000,0000,,And though each of us is unique,\Nour collective lives produce
Dialogue: 0,0:17:26.12,0:17:29.88,Default,,0000,0000,0000,,averages that can\Ncharacterise whole populations.
Dialogue: 0,0:17:41.28,0:17:45.36,Default,,0000,0000,0000,,I looked in my local newspaper\None week and saw a pensioner
Dialogue: 0,0:17:45.36,0:17:49.44,Default,,0000,0000,0000,,had accidentally put her foot on\Nthe accelerator
Dialogue: 0,0:17:49.44,0:17:52.56,Default,,0000,0000,0000,,and crushed her friend\Nagainst a wall.
Dialogue: 0,0:17:52.56,0:17:56.36,Default,,0000,0000,0000,,Devastating, hideous,\Nhorrible thing to happen.
Dialogue: 0,0:17:56.36,0:18:01.40,Default,,0000,0000,0000,,And then there was a second one about\Na young man who didn't have
Dialogue: 0,0:18:01.40,0:18:07.04,Default,,0000,0000,0000,,a driving licence, was driving a car\Nunder the influence of drugs\Nand alcohol
Dialogue: 0,0:18:07.04,0:18:10.32,Default,,0000,0000,0000,,and he bashed into a pedestrian\Nand killed him.
Dialogue: 0,0:18:10.32,0:18:15.56,Default,,0000,0000,0000,,What's remarkable, absolutely\Nremarkable, if you look at the number
Dialogue: 0,0:18:15.56,0:18:22.88,Default,,0000,0000,0000,,of people who die each year\Nin traffic crashes,\Nit's nearly a constant.
Dialogue: 0,0:18:22.88,0:18:24.48,Default,,0000,0000,0000,,What?
Dialogue: 0,0:18:24.48,0:18:31.68,Default,,0000,0000,0000,,All these individual events,\Nsomehow when you sum them all up\Nthere's the same number every year.
Dialogue: 0,0:18:31.68,0:18:35.08,Default,,0000,0000,0000,,And every year, two and a half\Ntimes as many men
Dialogue: 0,0:18:35.08,0:18:38.88,Default,,0000,0000,0000,,die in traffic crashes\Nas women, and it's a constant.
Dialogue: 0,0:18:38.88,0:18:44.32,Default,,0000,0000,0000,,And every year the rate in Belgium\Nis double the rate in England.
Dialogue: 0,0:18:44.32,0:18:47.16,Default,,0000,0000,0000,,There are these\Nremarkable regularities.
Dialogue: 0,0:18:47.16,0:18:54.80,Default,,0000,0000,0000,,So that these individual\Nparticular events sum up\Ninto a social phenomenon.
Dialogue: 0,0:18:56.56,0:18:58.12,Default,,0000,0000,0000,,Let's see what Sweden have done.
Dialogue: 0,0:18:58.12,0:19:01.56,Default,,0000,0000,0000,,We used to boast about fast social\Nprogress, that's where we were....
Dialogue: 0,0:19:01.56,0:19:05.24,Default,,0000,0000,0000,,'In my lectures, to tell stories\Nabout the changing world,
Dialogue: 0,0:19:05.24,0:19:08.12,Default,,0000,0000,0000,,'I use the averages\Nfrom entire countries,
Dialogue: 0,0:19:08.12,0:19:12.16,Default,,0000,0000,0000,,'whether the average of income,\Nchild mortality, family size
Dialogue: 0,0:19:12.16,0:19:13.36,Default,,0000,0000,0000,,'or carbon output.'
Dialogue: 0,0:19:13.36,0:19:16.20,Default,,0000,0000,0000,,OK, I give you Singapore.\NThe year I was born,
Dialogue: 0,0:19:16.20,0:19:20.56,Default,,0000,0000,0000,,Singapore had twice the child\Nmortality of Sweden, the most\Ntropical country in the world,
Dialogue: 0,0:19:20.56,0:19:22.92,Default,,0000,0000,0000,,a marshland on\Nthe Equator, and here we go.
Dialogue: 0,0:19:22.92,0:19:25.16,Default,,0000,0000,0000,,It took a little time for them\Nto get independent,
Dialogue: 0,0:19:25.16,0:19:27.16,Default,,0000,0000,0000,,but then they started to grow\Ntheir economy,
Dialogue: 0,0:19:27.16,0:19:29.84,Default,,0000,0000,0000,,and they made the social investment,\Nthey got away malaria,
Dialogue: 0,0:19:29.84,0:19:33.36,Default,,0000,0000,0000,,they got a magnificent health system\Nthat beat both US and Sweden.
Dialogue: 0,0:19:33.36,0:19:37.60,Default,,0000,0000,0000,,We never thought it would happen\Nthat they would win over Sweden!
Dialogue: 0,0:19:37.60,0:19:40.52,Default,,0000,0000,0000,,LAUGHTER AND APPLAUSE
Dialogue: 0,0:19:40.52,0:19:46.40,Default,,0000,0000,0000,,But useful as averages are,\Nthey don't tell you the whole story.
Dialogue: 0,0:19:48.80,0:19:53.04,Default,,0000,0000,0000,,On average, Swedish people have\Nslightly less than two legs.
Dialogue: 0,0:19:53.04,0:19:57.56,Default,,0000,0000,0000,,This is because few people\Nonly have one leg or no legs,
Dialogue: 0,0:19:57.56,0:19:59.76,Default,,0000,0000,0000,,and no-one has three legs.
Dialogue: 0,0:19:59.76,0:20:06.24,Default,,0000,0000,0000,,So almost everybody in Sweden\Nhas more than\Nthe average number of legs.
Dialogue: 0,0:20:06.24,0:20:10.84,Default,,0000,0000,0000,,The variation in data is just\Nas important as the average.
Dialogue: 0,0:20:16.80,0:20:19.40,Default,,0000,0000,0000,,But how do you get\Na handle on variation?
Dialogue: 0,0:20:19.40,0:20:23.00,Default,,0000,0000,0000,,For this, you transform\Nnumbers into shapes.
Dialogue: 0,0:20:23.00,0:20:26.32,Default,,0000,0000,0000,,Let's look again at the number of\Nadult women in Sweden
Dialogue: 0,0:20:26.32,0:20:27.80,Default,,0000,0000,0000,,for different heights.
Dialogue: 0,0:20:27.80,0:20:31.80,Default,,0000,0000,0000,,Plotting the data as a shape\Nshows how much their heights
Dialogue: 0,0:20:31.80,0:20:36.40,Default,,0000,0000,0000,,vary from the average\Nand how wide that variation is.
Dialogue: 0,0:20:36.40,0:20:41.52,Default,,0000,0000,0000,,The shape a set of data makes\Nis called its distribution.
Dialogue: 0,0:20:41.52,0:20:46.08,Default,,0000,0000,0000,,This is the income distribution\Nof China, 1970.
Dialogue: 0,0:20:46.08,0:20:51.00,Default,,0000,0000,0000,,This is the income distribution\Nof the United States, 1970.
Dialogue: 0,0:20:51.00,0:20:54.08,Default,,0000,0000,0000,,Almost no overlap,\Nand what has happened?
Dialogue: 0,0:20:54.08,0:20:56.88,Default,,0000,0000,0000,,China is growing,\Nit's not so equal any longer,
Dialogue: 0,0:20:56.88,0:21:01.12,Default,,0000,0000,0000,,and it's appearing here\Noverlooking the United States.
Dialogue: 0,0:21:01.12,0:21:03.48,Default,,0000,0000,0000,,Almost like a ghost, isn't it?
Dialogue: 0,0:21:03.48,0:21:05.16,Default,,0000,0000,0000,,It's pretty scary.
Dialogue: 0,0:21:05.16,0:21:06.68,Default,,0000,0000,0000,,Rrrr!
Dialogue: 0,0:21:06.68,0:21:08.20,Default,,0000,0000,0000,,LAUGHTER
Dialogue: 0,0:21:17.16,0:21:21.28,Default,,0000,0000,0000,,The statisticians\Nwho first explored distribution
Dialogue: 0,0:21:21.28,0:21:25.76,Default,,0000,0000,0000,,discovered one shape\Nthat turned up again and again.
Dialogue: 0,0:21:25.76,0:21:28.12,Default,,0000,0000,0000,,The Victorian scholar\NFrancis Galton
Dialogue: 0,0:21:28.12,0:21:32.40,Default,,0000,0000,0000,,was so fascinated he built\Na machine that could reproduce it,
Dialogue: 0,0:21:32.40,0:21:36.08,Default,,0000,0000,0000,,and he found it fitted so many\Ndifferent sets of measurements
Dialogue: 0,0:21:36.08,0:21:38.64,Default,,0000,0000,0000,,that he named it\Nthe normal distribution.
Dialogue: 0,0:21:38.64,0:21:45.60,Default,,0000,0000,0000,,Whether it was people's arm spans,\Nlung capacities,
Dialogue: 0,0:21:45.60,0:21:47.40,Default,,0000,0000,0000,,or even their exam results,
Dialogue: 0,0:21:47.40,0:21:51.36,Default,,0000,0000,0000,,the normal distribution shape\Nrecurred time and time again.
Dialogue: 0,0:21:51.36,0:21:56.36,Default,,0000,0000,0000,,Other statisticians soon found\Nmany other regular shapes,
Dialogue: 0,0:21:56.36,0:22:01.36,Default,,0000,0000,0000,,each produced by particular kinds\Nof natural or social processes.
Dialogue: 0,0:22:01.36,0:22:05.40,Default,,0000,0000,0000,,And every statistician\Nhas their favourite.
Dialogue: 0,0:22:05.40,0:22:09.28,Default,,0000,0000,0000,,The Poisson distribution, the Poisson\Nshape is my favourite distribution.
Dialogue: 0,0:22:09.28,0:22:11.12,Default,,0000,0000,0000,,I think it's an absolute cracker.
Dialogue: 0,0:22:15.76,0:22:18.72,Default,,0000,0000,0000,,The Poisson shape\Ndescribes how likely it is
Dialogue: 0,0:22:18.72,0:22:21.68,Default,,0000,0000,0000,,that out-of-the-ordinary things\Nwill happen.
Dialogue: 0,0:22:21.68,0:22:24.52,Default,,0000,0000,0000,,Imagine a London bus stop where\Nwe know that on average
Dialogue: 0,0:22:24.52,0:22:26.28,Default,,0000,0000,0000,,we'll get three buses in an hour.
Dialogue: 0,0:22:26.28,0:22:29.28,Default,,0000,0000,0000,,We won't always get\Nthree buses, of course.
Dialogue: 0,0:22:29.28,0:22:33.48,Default,,0000,0000,0000,,Amazingly, the Poisson shape will\Nshow us the probability
Dialogue: 0,0:22:33.48,0:22:37.20,Default,,0000,0000,0000,,that in any given hour we will get\Nfour, five, or six buses,
Dialogue: 0,0:22:37.20,0:22:39.44,Default,,0000,0000,0000,,or no buses at all.
Dialogue: 0,0:22:40.72,0:22:43.48,Default,,0000,0000,0000,,The exact shape changes\Nwith the average.
Dialogue: 0,0:22:43.48,0:22:46.92,Default,,0000,0000,0000,,But whether it's how many people\Nwill win the lottery jackpot
Dialogue: 0,0:22:46.92,0:22:48.00,Default,,0000,0000,0000,,each week,
Dialogue: 0,0:22:48.00,0:22:51.20,Default,,0000,0000,0000,,or how many people will phone\Na call centre each minute,
Dialogue: 0,0:22:51.20,0:22:54.12,Default,,0000,0000,0000,,the Poisson shape\Nwill give the probabilities.
Dialogue: 0,0:22:57.24,0:23:01.24,Default,,0000,0000,0000,,The wonderful example where this was\Napplied to in the late 19th century
Dialogue: 0,0:23:01.24,0:23:04.40,Default,,0000,0000,0000,,was to count each year the number of\NPrussian officers,
Dialogue: 0,0:23:04.40,0:23:07.52,Default,,0000,0000,0000,,cavalry officers, who were kicked\Nto death by their horses.
Dialogue: 0,0:23:07.52,0:23:10.24,Default,,0000,0000,0000,,Now, some years there were none,\Nsome years there were one,
Dialogue: 0,0:23:10.24,0:23:13.88,Default,,0000,0000,0000,,some years there were two,\Nup to seven, I think,\None particularly bad year.
Dialogue: 0,0:23:13.88,0:23:16.68,Default,,0000,0000,0000,,But with this distribution,\Nhowever many years there were
Dialogue: 0,0:23:16.68,0:23:19.64,Default,,0000,0000,0000,,with nought, one, two, three,\Nfour Prussian cavalry officers
Dialogue: 0,0:23:19.64,0:23:23.88,Default,,0000,0000,0000,,kicked to death by their horses,\Nbeautifully obeyed\Nthe Poisson distribution.
Dialogue: 0,0:23:42.80,0:23:48.52,Default,,0000,0000,0000,,So statisticians use shapes to\Nreveal the patterns in the data.
Dialogue: 0,0:23:48.52,0:23:51.00,Default,,0000,0000,0000,,But we also use images of all kinds
Dialogue: 0,0:23:51.00,0:23:54.48,Default,,0000,0000,0000,,to communicate statistics\Nto a wider public.
Dialogue: 0,0:23:54.48,0:23:57.32,Default,,0000,0000,0000,,Because if the story in the numbers
Dialogue: 0,0:23:57.32,0:24:02.92,Default,,0000,0000,0000,,is told by a beautiful and clever\Nimage, then everyone understands.
Dialogue: 0,0:24:02.92,0:24:09.64,Default,,0000,0000,0000,,Of the pioneers\Nof statistical graphics,\Nmy favourite is Florence Nightingale.
Dialogue: 0,0:24:24.28,0:24:27.12,Default,,0000,0000,0000,,There are not many people who realise\Nthat she was known
Dialogue: 0,0:24:27.12,0:24:30.52,Default,,0000,0000,0000,,as a passionate statistician\Nand not just the Lady of the Lamp.
Dialogue: 0,0:24:30.52,0:24:34.72,Default,,0000,0000,0000,,She said that "to understand God's\Nthoughts, we must study statistics,
Dialogue: 0,0:24:34.72,0:24:37.08,Default,,0000,0000,0000,,"for these are\Nthe measure of His purpose."
Dialogue: 0,0:24:37.08,0:24:40.52,Default,,0000,0000,0000,,Statistics was for her a religious\Nduty and moral imperative.
Dialogue: 0,0:24:42.08,0:24:45.36,Default,,0000,0000,0000,,When Florence was nine years old\Nshe started collecting data.
Dialogue: 0,0:24:45.36,0:24:48.32,Default,,0000,0000,0000,,Her data was different\Nfruits and vegetables she found.
Dialogue: 0,0:24:48.32,0:24:50.08,Default,,0000,0000,0000,,Put them into different tables.
Dialogue: 0,0:24:50.08,0:24:52.64,Default,,0000,0000,0000,,Trying to organise them\Nin some standard form.
Dialogue: 0,0:24:52.64,0:24:55.64,Default,,0000,0000,0000,,And so we have one of Nightingale's\Nfirst statistical tables
Dialogue: 0,0:24:55.64,0:24:57.44,Default,,0000,0000,0000,,at the age of nine.
Dialogue: 0,0:25:04.36,0:25:11.44,Default,,0000,0000,0000,,In the mid 1850s Florence\NNightingale went to the Crimea to\Ncare for British casualties of war.
Dialogue: 0,0:25:11.44,0:25:14.40,Default,,0000,0000,0000,,She was horrified by\Nwhat she discovered.
Dialogue: 0,0:25:14.40,0:25:19.92,Default,,0000,0000,0000,,For all the soldiers being blown\Nto bits on the battlefield,\Nthere were many, many more soldiers
Dialogue: 0,0:25:19.92,0:25:25.20,Default,,0000,0000,0000,,dying from diseases they caught\Nin the army's filthy hospitals.
Dialogue: 0,0:25:25.20,0:25:29.12,Default,,0000,0000,0000,,So Florence Nightingale\Nbegan counting the dead.
Dialogue: 0,0:25:29.12,0:25:34.92,Default,,0000,0000,0000,,For two years she recorded\Nmortality data in meticulous detail.
Dialogue: 0,0:25:34.92,0:25:39.12,Default,,0000,0000,0000,,When the war was over she persuaded\Nthe government to set up
Dialogue: 0,0:25:39.12,0:25:41.36,Default,,0000,0000,0000,,a Royal Commission of Inquiry,
Dialogue: 0,0:25:41.36,0:25:44.68,Default,,0000,0000,0000,,and gathered her data\Nin a devastating report.
Dialogue: 0,0:25:44.68,0:25:48.48,Default,,0000,0000,0000,,What has cemented her place in\Nthe statistical history books
Dialogue: 0,0:25:48.48,0:25:50.12,Default,,0000,0000,0000,,are the graphics she used.
Dialogue: 0,0:25:50.12,0:25:53.96,Default,,0000,0000,0000,,And one in particular,\Nthe polar area graph.
Dialogue: 0,0:25:53.96,0:25:58.68,Default,,0000,0000,0000,,For each month of the war,\Na huge blue wedge represented
Dialogue: 0,0:25:58.68,0:26:02.20,Default,,0000,0000,0000,,the soldiers who had died\Nfrom preventable diseases.
Dialogue: 0,0:26:02.20,0:26:05.56,Default,,0000,0000,0000,,The much smaller red wedges were\Ndeaths from wounds,
Dialogue: 0,0:26:05.56,0:26:10.60,Default,,0000,0000,0000,,and the black wedges were deaths\Nfrom accidents and other causes.
Dialogue: 0,0:26:10.60,0:26:17.04,Default,,0000,0000,0000,,Nightingale's graphics were so clear\Nthey were impossible to ignore.
Dialogue: 0,0:26:17.04,0:26:19.36,Default,,0000,0000,0000,,The usual thing around\NFlorence Nightingale's time
Dialogue: 0,0:26:19.36,0:26:23.92,Default,,0000,0000,0000,,was just to produce tables and\Ntables of figures - absolutely\Nreally tedious stuff that,
Dialogue: 0,0:26:23.92,0:26:26.32,Default,,0000,0000,0000,,unless you're an absolutely dedicated\Nstatistician,
Dialogue: 0,0:26:26.32,0:26:29.24,Default,,0000,0000,0000,,it's really quite difficult to spot\Nthe patterns quite naturally.
Dialogue: 0,0:26:29.24,0:26:33.48,Default,,0000,0000,0000,,But visualisations, they tell a\Nstory, they tell a story immediately.
Dialogue: 0,0:26:33.48,0:26:38.48,Default,,0000,0000,0000,,And the use of colour\Nand the use of shape can\Nreally tell a powerful story.
Dialogue: 0,0:26:38.48,0:26:41.28,Default,,0000,0000,0000,,And nowadays of course\Nwe can make things move as well.
Dialogue: 0,0:26:41.28,0:26:44.32,Default,,0000,0000,0000,,Florence Nightingale would have\Nloved to have played with...
Dialogue: 0,0:26:44.32,0:26:48.80,Default,,0000,0000,0000,,She would have\Nproduced wonderful animations,\NI'm absolutely certain of it.
Dialogue: 0,0:26:50.88,0:26:54.80,Default,,0000,0000,0000,,Today, 150 years on,\NNightingale's graphics
Dialogue: 0,0:26:54.80,0:26:57.80,Default,,0000,0000,0000,,are rightly regarded as a classic.
Dialogue: 0,0:26:57.80,0:27:00.60,Default,,0000,0000,0000,,They led to a revolution\Nin nursing, health care
Dialogue: 0,0:27:00.60,0:27:05.88,Default,,0000,0000,0000,,and hygiene in hospitals worldwide,\Nwhich saved innumerable lives.
Dialogue: 0,0:27:07.40,0:27:11.04,Default,,0000,0000,0000,,And statistical graphics has\Nbecome an art form of its very own,
Dialogue: 0,0:27:11.04,0:27:16.28,Default,,0000,0000,0000,,led by designers who are\Npassionate about visualising data.
Dialogue: 0,0:27:24.64,0:27:27.12,Default,,0000,0000,0000,,This is the Billion Pound-O-Gram.
Dialogue: 0,0:27:27.12,0:27:29.12,Default,,0000,0000,0000,,This image arose out of frustration
Dialogue: 0,0:27:29.12,0:27:32.28,Default,,0000,0000,0000,,with the reporting of billion pound\Namounts in the media.
Dialogue: 0,0:27:32.28,0:27:34.40,Default,,0000,0000,0000,,£500 billion pounds for this war.
Dialogue: 0,0:27:34.40,0:27:36.00,Default,,0000,0000,0000,,£50 billion for this oil spill.
Dialogue: 0,0:27:36.00,0:27:39.44,Default,,0000,0000,0000,,It doesn't make sense -\Nthe numbers are too enormous\Nto get your mind round.
Dialogue: 0,0:27:39.44,0:27:43.52,Default,,0000,0000,0000,,So I scraped all this data\Nfrom various news sources\Nand created this diagram.
Dialogue: 0,0:27:43.52,0:27:48.68,Default,,0000,0000,0000,,So the\Nsquares here are scaled according\Nto the billion pound amounts.
Dialogue: 0,0:27:48.68,0:27:51.84,Default,,0000,0000,0000,,When you see numbers visualised\Nlike this
Dialogue: 0,0:27:51.84,0:27:54.24,Default,,0000,0000,0000,,you start to have a different\Nrelationship with them.
Dialogue: 0,0:27:54.24,0:27:56.84,Default,,0000,0000,0000,,You can start to see the patterns,\Nand the scale of them.
Dialogue: 0,0:27:56.84,0:27:59.60,Default,,0000,0000,0000,,Here in the corner,\Nthis little square - £37 billion.
Dialogue: 0,0:27:59.60,0:28:02.80,Default,,0000,0000,0000,,This was the predicted cost\Nof the Iraq war in 2003.
Dialogue: 0,0:28:02.80,0:28:06.48,Default,,0000,0000,0000,,As you can see it's grown\Nexponentially over the last few years
Dialogue: 0,0:28:06.48,0:28:10.56,Default,,0000,0000,0000,,and the total cost now is\Naround about £2,500 billion.
Dialogue: 0,0:28:10.56,0:28:13.00,Default,,0000,0000,0000,,It's funny because when\Nyou visualise statistics
Dialogue: 0,0:28:13.00,0:28:15.36,Default,,0000,0000,0000,,you understand them,\Nand when you understand them
Dialogue: 0,0:28:15.36,0:28:18.40,Default,,0000,0000,0000,,you can really start to put things\Nin perspective.
Dialogue: 0,0:28:23.96,0:28:27.88,Default,,0000,0000,0000,,Visualisation is right at\Nthe heart of my own work too.
Dialogue: 0,0:28:27.88,0:28:30.16,Default,,0000,0000,0000,,I teach global health.
Dialogue: 0,0:28:30.16,0:28:33.84,Default,,0000,0000,0000,,And I know having the data\Nis not enough -
Dialogue: 0,0:28:33.84,0:28:39.16,Default,,0000,0000,0000,,I have to show it in ways people\Nboth enjoy and understand.
Dialogue: 0,0:28:39.16,0:28:42.96,Default,,0000,0000,0000,,Now I'm going to try something\NI've never done before.
Dialogue: 0,0:28:42.96,0:28:45.96,Default,,0000,0000,0000,,Animating the data in real space,
Dialogue: 0,0:28:45.96,0:28:50.48,Default,,0000,0000,0000,,with a bit of technical\Nassistance from the crew.
Dialogue: 0,0:28:50.48,0:28:52.24,Default,,0000,0000,0000,,So here we go.
Dialogue: 0,0:28:52.24,0:28:54.20,Default,,0000,0000,0000,,First, an axis for health.
Dialogue: 0,0:28:54.20,0:28:58.92,Default,,0000,0000,0000,,Life expectancy\Nfrom 25 years to 75 years.
Dialogue: 0,0:28:58.92,0:29:01.44,Default,,0000,0000,0000,,And down here an axis for wealth.
Dialogue: 0,0:29:01.44,0:29:06.72,Default,,0000,0000,0000,,Income per person -\N400, 4,000, 40,000.
Dialogue: 0,0:29:06.72,0:29:10.48,Default,,0000,0000,0000,,So down here is poor and sick.
Dialogue: 0,0:29:10.48,0:29:14.28,Default,,0000,0000,0000,,And up here is rich and healthy.
Dialogue: 0,0:29:14.28,0:29:18.32,Default,,0000,0000,0000,,Now I'm going to show you the world
Dialogue: 0,0:29:18.32,0:29:21.08,Default,,0000,0000,0000,,200 years ago, in 1810.
Dialogue: 0,0:29:21.08,0:29:22.88,Default,,0000,0000,0000,,Here come all the countries.
Dialogue: 0,0:29:22.88,0:29:26.20,Default,,0000,0000,0000,,Europe, brown;\NAsia, red; Middle East, green;
Dialogue: 0,0:29:26.20,0:29:29.44,Default,,0000,0000,0000,,Africa south of the Sahara,\Nblue; and the Americas, yellow.
Dialogue: 0,0:29:29.44,0:29:33.76,Default,,0000,0000,0000,,And the size of the country bubble\Nshows the size of the population.
Dialogue: 0,0:29:33.76,0:29:37.56,Default,,0000,0000,0000,,In 1810, it was pretty crowded\Ndown there, wasn't it?
Dialogue: 0,0:29:37.56,0:29:39.76,Default,,0000,0000,0000,,All countries were sick and poor.
Dialogue: 0,0:29:39.76,0:29:43.36,Default,,0000,0000,0000,,Life expectancy\Nwas below 40 in all countries.
Dialogue: 0,0:29:43.36,0:29:48.68,Default,,0000,0000,0000,,And only UK and the Netherlands were\Nslightly better off. But not much.
Dialogue: 0,0:29:48.68,0:29:52.52,Default,,0000,0000,0000,,And now I start the world.
Dialogue: 0,0:29:52.52,0:29:56.84,Default,,0000,0000,0000,,The industrial revolution makes\Ncountries in Europe and elsewhere
Dialogue: 0,0:29:56.84,0:29:59.04,Default,,0000,0000,0000,,move away from the rest.
Dialogue: 0,0:29:59.04,0:30:02.28,Default,,0000,0000,0000,,But the colonized countries\Nin Asia and Africa,
Dialogue: 0,0:30:02.28,0:30:04.04,Default,,0000,0000,0000,,they are stuck down there.
Dialogue: 0,0:30:04.04,0:30:08.20,Default,,0000,0000,0000,,And eventually the Western countries\Nget healthier and healthier.
Dialogue: 0,0:30:08.20,0:30:13.32,Default,,0000,0000,0000,,And now we slow down to show\Nthe impact of the First World War
Dialogue: 0,0:30:13.32,0:30:15.88,Default,,0000,0000,0000,,and the Spanish flu epidemic.
Dialogue: 0,0:30:15.88,0:30:18.32,Default,,0000,0000,0000,,What a catastrophe!
Dialogue: 0,0:30:18.32,0:30:22.64,Default,,0000,0000,0000,,And now I speed up through\Nthe 1920s and the 1930s and,
Dialogue: 0,0:30:22.64,0:30:24.40,Default,,0000,0000,0000,,in spite of the Great Depression,
Dialogue: 0,0:30:24.40,0:30:27.80,Default,,0000,0000,0000,,Western countries forge on towards\Ngreater wealth and health.
Dialogue: 0,0:30:27.80,0:30:29.88,Default,,0000,0000,0000,,Japan and some others try to follow.
Dialogue: 0,0:30:29.88,0:30:32.56,Default,,0000,0000,0000,,But most countries stay down here.
Dialogue: 0,0:30:32.56,0:30:35.64,Default,,0000,0000,0000,,And after the tragedies\Nof the Second World War,
Dialogue: 0,0:30:35.64,0:30:39.40,Default,,0000,0000,0000,,we stop a bit to look\Nat the world in 1948.
Dialogue: 0,0:30:39.40,0:30:42.08,Default,,0000,0000,0000,,1948 was a great year.
Dialogue: 0,0:30:42.08,0:30:43.28,Default,,0000,0000,0000,,The war was over,
Dialogue: 0,0:30:43.28,0:30:48.00,Default,,0000,0000,0000,,Sweden topped the medal table at\Nthe Winter Olympics and I was born.
Dialogue: 0,0:30:48.00,0:30:51.28,Default,,0000,0000,0000,,But the differences between\Nthe countries of the world
Dialogue: 0,0:30:51.28,0:30:52.68,Default,,0000,0000,0000,,was wider than ever.
Dialogue: 0,0:30:52.68,0:30:54.96,Default,,0000,0000,0000,,United States was in the front.
Dialogue: 0,0:30:54.96,0:30:56.84,Default,,0000,0000,0000,,Japan was catching up.
Dialogue: 0,0:30:56.84,0:30:58.40,Default,,0000,0000,0000,,Brazil was way behind,
Dialogue: 0,0:30:58.40,0:31:03.04,Default,,0000,0000,0000,,Iran was getting a little richer\Nfrom oil but still had short lives.
Dialogue: 0,0:31:03.04,0:31:05.16,Default,,0000,0000,0000,,And the Asian giants...
Dialogue: 0,0:31:05.16,0:31:08.72,Default,,0000,0000,0000,,China, India, Pakistan, Bangladesh,\Nand Indonesia,
Dialogue: 0,0:31:08.72,0:31:11.36,Default,,0000,0000,0000,,they were still\Npoor and sick down here.
Dialogue: 0,0:31:11.36,0:31:14.36,Default,,0000,0000,0000,,But look what was about to happen!\NHere we go again.
Dialogue: 0,0:31:14.36,0:31:18.64,Default,,0000,0000,0000,,In my lifetime, former colonies\Ngained independence and then finally
Dialogue: 0,0:31:18.64,0:31:22.64,Default,,0000,0000,0000,,they started to get healthier\Nand healthier and healthier.
Dialogue: 0,0:31:22.64,0:31:26.08,Default,,0000,0000,0000,,And in the 1970s, then countries\Nin Asia and Latin America
Dialogue: 0,0:31:26.08,0:31:28.96,Default,,0000,0000,0000,,started to catch up\Nwith the Western countries.
Dialogue: 0,0:31:28.96,0:31:31.24,Default,,0000,0000,0000,,They became the emerging economies.
Dialogue: 0,0:31:31.24,0:31:32.64,Default,,0000,0000,0000,,Some in Africa follows,
Dialogue: 0,0:31:32.64,0:31:36.44,Default,,0000,0000,0000,,some Africans were stuck in civil\Nwar, and others were hit by HIV.
Dialogue: 0,0:31:36.44,0:31:41.84,Default,,0000,0000,0000,,And now we can see the world\Nin the most up-to-date statistics.
Dialogue: 0,0:31:42.84,0:31:45.48,Default,,0000,0000,0000,,Most people today\Nlive in the middle.
Dialogue: 0,0:31:45.48,0:31:48.08,Default,,0000,0000,0000,,But there is huge difference\Nat the same time
Dialogue: 0,0:31:48.08,0:31:51.52,Default,,0000,0000,0000,,between the best-off countries\Nand the worst-off countries.
Dialogue: 0,0:31:51.52,0:31:54.52,Default,,0000,0000,0000,,And there are also huge\Ninequalities within countries.
Dialogue: 0,0:31:54.52,0:31:59.00,Default,,0000,0000,0000,,These bubbles show country averages\Nbut I can split them.
Dialogue: 0,0:31:59.00,0:32:02.12,Default,,0000,0000,0000,,Take China. I can split it\Ninto provinces.
Dialogue: 0,0:32:02.12,0:32:05.12,Default,,0000,0000,0000,,There goes Shanghai...
Dialogue: 0,0:32:05.12,0:32:08.00,Default,,0000,0000,0000,,It has the same health\Nand wealth as Italy today.
Dialogue: 0,0:32:08.00,0:32:11.24,Default,,0000,0000,0000,,And there\Nis the poor inland province Guizhou,
Dialogue: 0,0:32:11.24,0:32:12.68,Default,,0000,0000,0000,,it is like Pakistan.
Dialogue: 0,0:32:12.68,0:32:18.80,Default,,0000,0000,0000,,And if I split it further, the rural\Nparts are like Ghana in Africa.
Dialogue: 0,0:32:19.80,0:32:23.16,Default,,0000,0000,0000,,And yet, despite the enormous\Ndisparities today,
Dialogue: 0,0:32:23.16,0:32:27.24,Default,,0000,0000,0000,,we have seen 200 years\Nof remarkable progress!
Dialogue: 0,0:32:27.24,0:32:31.72,Default,,0000,0000,0000,,That huge historical gap between\Nthe west and the rest is now closing.
Dialogue: 0,0:32:31.72,0:32:35.64,Default,,0000,0000,0000,,We have become an entirely\Nnew, converging world.
Dialogue: 0,0:32:35.64,0:32:37.96,Default,,0000,0000,0000,,And I see a clear trend\Ninto the future.
Dialogue: 0,0:32:37.96,0:32:40.84,Default,,0000,0000,0000,,With aid, trade, green\Ntechnology and peace,
Dialogue: 0,0:32:40.84,0:32:43.72,Default,,0000,0000,0000,,it's fully possible\Nthat everyone can make it
Dialogue: 0,0:32:43.72,0:32:45.64,Default,,0000,0000,0000,,to the healthy, wealthy corner.
Dialogue: 0,0:32:48.00,0:32:51.36,Default,,0000,0000,0000,,Well, what you've just seen\Nin the last few minutes
Dialogue: 0,0:32:51.36,0:32:56.52,Default,,0000,0000,0000,,is a story of 200 countries\Nshown over 200 years and beyond.
Dialogue: 0,0:32:56.52,0:33:00.96,Default,,0000,0000,0000,,It involved plotting\N120,000 numbers.
Dialogue: 0,0:33:00.96,0:33:02.56,Default,,0000,0000,0000,,Pretty neat, huh?
Dialogue: 0,0:33:07.96,0:33:13.12,Default,,0000,0000,0000,,So, with statistics, we can begin\Nto see things as they really are.
Dialogue: 0,0:33:13.12,0:33:18.20,Default,,0000,0000,0000,,From tables of data to averages,\Ndistributions and visualisations,
Dialogue: 0,0:33:18.20,0:33:22.64,Default,,0000,0000,0000,,statistics gives us a\Nclear description of the world.
Dialogue: 0,0:33:22.64,0:33:28.20,Default,,0000,0000,0000,,But, with statistics, we can\Nnot only discover WHAT is happening
Dialogue: 0,0:33:28.20,0:33:30.52,Default,,0000,0000,0000,,but also explore WHY,
Dialogue: 0,0:33:30.52,0:33:34.48,Default,,0000,0000,0000,,by using the powerful analytical\Nmethod - correlation.
Dialogue: 0,0:33:35.48,0:33:38.40,Default,,0000,0000,0000,,Just looking at one thing at a\Ntime doesn't tell you very much.
Dialogue: 0,0:33:38.40,0:33:41.28,Default,,0000,0000,0000,,You've got to look at the\Nrelationships between things,
Dialogue: 0,0:33:41.28,0:33:43.36,Default,,0000,0000,0000,,how they change,\Nhow they vary together.
Dialogue: 0,0:33:43.36,0:33:45.36,Default,,0000,0000,0000,,That's what correlation is about.
Dialogue: 0,0:33:45.36,0:33:48.32,Default,,0000,0000,0000,,That's how you start trying\Nto understand the processes
Dialogue: 0,0:33:48.32,0:33:50.96,Default,,0000,0000,0000,,that are really going on\Nin the world and society.
Dialogue: 0,0:33:52.48,0:33:57.00,Default,,0000,0000,0000,,Most of us today would recognise\Nthat crime correlates to poverty,
Dialogue: 0,0:33:57.00,0:34:00.20,Default,,0000,0000,0000,,that infection correlates\Nto poor sanitation,
Dialogue: 0,0:34:00.20,0:34:02.60,Default,,0000,0000,0000,,and that knowledge of statistics\Ncorrelates
Dialogue: 0,0:34:02.60,0:34:05.04,Default,,0000,0000,0000,,to being great at dancing!
Dialogue: 0,0:34:06.56,0:34:10.20,Default,,0000,0000,0000,,Correlations can be very tricky.
Dialogue: 0,0:34:10.20,0:34:12.96,Default,,0000,0000,0000,,I got a joke about\Nsilly correlations.
Dialogue: 0,0:34:12.96,0:34:15.84,Default,,0000,0000,0000,,There was this American who\Nwas afraid of heart attack.
Dialogue: 0,0:34:15.84,0:34:19.92,Default,,0000,0000,0000,,He found out that\Nthe Japanese ate very little fat
Dialogue: 0,0:34:19.92,0:34:22.32,Default,,0000,0000,0000,,and almost didn't drink wine,
Dialogue: 0,0:34:22.32,0:34:25.52,Default,,0000,0000,0000,,but they had much less\Nheart attacks than the Americans.
Dialogue: 0,0:34:25.52,0:34:28.64,Default,,0000,0000,0000,,But, on the other hand,\Nhe also found out that the French
Dialogue: 0,0:34:28.64,0:34:35.08,Default,,0000,0000,0000,,eat as much fat as the Americans\Nand they drink much more wine but\Nthey also have less heart attacks.
Dialogue: 0,0:34:35.08,0:34:40.84,Default,,0000,0000,0000,,So he concluded that what kills you\Nis speaking English.
Dialogue: 0,0:34:40.84,0:34:43.92,Default,,0000,0000,0000,,# Smoke, smoke,\Nsmoke that cigarette
Dialogue: 0,0:34:43.92,0:34:48.00,Default,,0000,0000,0000,,# Puff, puff, puff and if you\Nsmoke yourself to death... #
Dialogue: 0,0:34:48.00,0:34:51.92,Default,,0000,0000,0000,,The time, the pace,\Nthe cigarette. Weights Tilt.
Dialogue: 0,0:34:51.92,0:34:56.20,Default,,0000,0000,0000,,The best example of a really\Nground-breaking correlation
Dialogue: 0,0:34:56.20,0:35:01.64,Default,,0000,0000,0000,,is the link that was established\Nin the 1950s between\Nsmoking and lung cancer.
Dialogue: 0,0:35:01.64,0:35:07.04,Default,,0000,0000,0000,,Not long after the Second World War,\Na British doctor, Richard Doll,
Dialogue: 0,0:35:07.04,0:35:11.04,Default,,0000,0000,0000,,investigated lung cancer patients\Nin 20 London hospitals.
Dialogue: 0,0:35:11.04,0:35:15.40,Default,,0000,0000,0000,,And he became certain\Nthat the only thing they had\Nin common was smoking.
Dialogue: 0,0:35:15.40,0:35:18.28,Default,,0000,0000,0000,,So certain,\Nthat he stopped smoking himself.
Dialogue: 0,0:35:18.28,0:35:22.16,Default,,0000,0000,0000,,But other people weren't so sure.
Dialogue: 0,0:35:22.16,0:35:25.40,Default,,0000,0000,0000,,A lot of the discussion\Nof the early data,
Dialogue: 0,0:35:25.40,0:35:29.12,Default,,0000,0000,0000,,linking smoking to lung cancer, said,\N"It's not the smoking, surely,
Dialogue: 0,0:35:29.12,0:35:32.60,Default,,0000,0000,0000,,"that thing we've done all our lives,\Nthat can't be bad for you.
Dialogue: 0,0:35:32.60,0:35:35.00,Default,,0000,0000,0000,,"Maybe it's genes.
Dialogue: 0,0:35:35.00,0:35:39.08,Default,,0000,0000,0000,,"Maybe people who are genetically\Npredisposed to get lung cancer
Dialogue: 0,0:35:39.08,0:35:43.84,Default,,0000,0000,0000,,"are also genetically\Npredisposed to smoke."
Dialogue: 0,0:35:43.84,0:35:47.36,Default,,0000,0000,0000,,"Maybe it's not the smoking,\Nmaybe it's air pollution -
Dialogue: 0,0:35:47.36,0:35:52.52,Default,,0000,0000,0000,,"that smokers are somehow\Nmore exposed to air pollution\Nthan non-smokers.
Dialogue: 0,0:35:52.52,0:35:56.28,Default,,0000,0000,0000,,"Maybe it's not smoking,\Nmaybe it's poverty."
Dialogue: 0,0:35:56.28,0:36:00.72,Default,,0000,0000,0000,,So now we've got three alternative\Nexplanations, apart from chance.
Dialogue: 0,0:36:02.24,0:36:06.76,Default,,0000,0000,0000,,To verify his correlation\Ndid imply cause and effect.
Dialogue: 0,0:36:06.76,0:36:10.68,Default,,0000,0000,0000,,Richard Doll created the biggest\Nstatistical study of smoking yet.
Dialogue: 0,0:36:10.68,0:36:14.68,Default,,0000,0000,0000,,He began tracking the lives\Nof 40,000 British doctors,
Dialogue: 0,0:36:14.68,0:36:17.00,Default,,0000,0000,0000,,some of whom smoked\Nand some of whom didn't,
Dialogue: 0,0:36:17.00,0:36:19.44,Default,,0000,0000,0000,,and gathered enough data
Dialogue: 0,0:36:19.44,0:36:22.00,Default,,0000,0000,0000,,to correlate the amount\Nthe doctors smoked
Dialogue: 0,0:36:22.00,0:36:24.92,Default,,0000,0000,0000,,with their likelihood\Nof getting cancer.
Dialogue: 0,0:36:24.92,0:36:30.12,Default,,0000,0000,0000,,Eventually, he not only\Nshowed a correlation between\Nsmoking and lung cancer,
Dialogue: 0,0:36:30.12,0:36:35.80,Default,,0000,0000,0000,,but also a correlation\Nbetween stopping smoking\Nand reducing the risk.
Dialogue: 0,0:36:35.80,0:36:37.76,Default,,0000,0000,0000,,This was science at its best.
Dialogue: 0,0:36:39.76,0:36:44.00,Default,,0000,0000,0000,,What correlations do not replace\Nis human thought.
Dialogue: 0,0:36:44.00,0:36:46.76,Default,,0000,0000,0000,,You've got to think\Nabout what it means.
Dialogue: 0,0:36:46.76,0:36:50.48,Default,,0000,0000,0000,,What a good scientist does,\Nif he comes with a correlation,
Dialogue: 0,0:36:50.48,0:36:55.96,Default,,0000,0000,0000,,is try as hard as she or he\Npossibly can to disprove it,
Dialogue: 0,0:36:55.96,0:37:00.20,Default,,0000,0000,0000,,to break it down, to get rid of it,\Nto try and refute it.
Dialogue: 0,0:37:00.20,0:37:05.44,Default,,0000,0000,0000,,And if it withstands\Nall those efforts at demolishing it
Dialogue: 0,0:37:05.44,0:37:10.76,Default,,0000,0000,0000,,and it is still standing up then,\Ncautiously, you say, "We really\Nmight have something here."
Dialogue: 0,0:37:26.72,0:37:32.84,Default,,0000,0000,0000,,However brilliant the scientist,\Ndata is still the oxygen of science.
Dialogue: 0,0:37:32.84,0:37:39.32,Default,,0000,0000,0000,,The good news is that the more we\Nhave, the more correlations we'll\Nfind, the more theories we'll test,
Dialogue: 0,0:37:39.32,0:37:42.24,Default,,0000,0000,0000,,and the more discoveries\Nwe're likely to make.
Dialogue: 0,0:37:46.16,0:37:53.44,Default,,0000,0000,0000,,And history shows how our total sum\Nof information grows in huge leaps\Nas we develop new technologies.
Dialogue: 0,0:37:53.44,0:38:00.00,Default,,0000,0000,0000,,The invention of the\Nprinting press kicked off the first\Ndata and information explosion.
Dialogue: 0,0:38:00.00,0:38:06.00,Default,,0000,0000,0000,,If you piled up all the books that\Nhad been printed by the year 1700,
Dialogue: 0,0:38:06.00,0:38:11.20,Default,,0000,0000,0000,,they would make 60 stacks\Neach as high as Mount Everest.
Dialogue: 0,0:38:12.88,0:38:15.36,Default,,0000,0000,0000,,Then, starting in the 19th century,
Dialogue: 0,0:38:15.36,0:38:19.88,Default,,0000,0000,0000,,there came a second information\Nrevolution with the telegraph,
Dialogue: 0,0:38:19.88,0:38:23.96,Default,,0000,0000,0000,,gramophone and camera.\NAnd later radio and TV.
Dialogue: 0,0:38:23.96,0:38:28.20,Default,,0000,0000,0000,,The total amount\Nof information exploded.
Dialogue: 0,0:38:28.20,0:38:35.20,Default,,0000,0000,0000,,And by the 1950s\Nthe information available to us all\Nhad multiplied 6,000 times.
Dialogue: 0,0:38:35.20,0:38:41.44,Default,,0000,0000,0000,,Then, thanks to the computer and\Nlater the internet, we went digital.
Dialogue: 0,0:38:41.44,0:38:47.20,Default,,0000,0000,0000,,And the amount of data we have now\Nis unimaginably vast.
Dialogue: 0,0:38:49.92,0:38:55.08,Default,,0000,0000,0000,,A single letter printed in a book\Nis equivalent to a byte of data.
Dialogue: 0,0:38:55.08,0:38:58.72,Default,,0000,0000,0000,,A printed page\Nequals a kilobyte or two.
Dialogue: 0,0:39:01.96,0:39:06.24,Default,,0000,0000,0000,,Five megabytes is enough for\Nthe complete works of Shakespeare.
Dialogue: 0,0:39:08.00,0:39:11.68,Default,,0000,0000,0000,,10 gigabytes - that's a DVD movie.
Dialogue: 0,0:39:16.84,0:39:23.36,Default,,0000,0000,0000,,Two terabytes\Nis the tens of millions of photos\Nadded to Facebook every day.
Dialogue: 0,0:39:24.88,0:39:32.20,Default,,0000,0000,0000,,Ten petabytes is the data recorded\Nevery second by the world's\Nlargest particle accelerator.
Dialogue: 0,0:39:32.20,0:39:35.80,Default,,0000,0000,0000,,So much\Nonly a tiny fraction is kept.
Dialogue: 0,0:39:35.80,0:39:43.44,Default,,0000,0000,0000,,Six exabytes is what you'd have\Nif you sequenced the genomes\Nof every single person on Earth.
Dialogue: 0,0:39:48.68,0:39:50.52,Default,,0000,0000,0000,,But really, that's nothing.
Dialogue: 0,0:39:50.52,0:39:55.08,Default,,0000,0000,0000,,In 2009, the internet\Nadded up to 500 exabytes.
Dialogue: 0,0:39:55.08,0:40:02.12,Default,,0000,0000,0000,,In 2010, in just one year, that will\Ndouble to more than one zettabyte!
Dialogue: 0,0:40:06.36,0:40:14.00,Default,,0000,0000,0000,,Back in the real world, if we\Nturned all this data into print\Nit would make 90 stacks of books,
Dialogue: 0,0:40:14.00,0:40:18.56,Default,,0000,0000,0000,,each reaching from here\Nall the way to the sun!
Dialogue: 0,0:40:18.56,0:40:23.60,Default,,0000,0000,0000,,The data deluge is staggering,\Nbut, with today's computers
Dialogue: 0,0:40:23.60,0:40:28.20,Default,,0000,0000,0000,,and statistics,\NI'm confident we can handle it.
Dialogue: 0,0:40:28.20,0:40:31.40,Default,,0000,0000,0000,,When it comes to all the data\Non the internet,
Dialogue: 0,0:40:31.40,0:40:33.76,Default,,0000,0000,0000,,the powerhouse\Nof statistical analysis
Dialogue: 0,0:40:33.76,0:40:37.56,Default,,0000,0000,0000,,is the Silicon Valley giant Google.
Dialogue: 0,0:40:44.00,0:40:50.60,Default,,0000,0000,0000,,The average person over their\Nlifetime is exposed to about 100\Nmillion words of conversation.
Dialogue: 0,0:40:50.60,0:40:54.84,Default,,0000,0000,0000,,And so if you multiple that by the\Nsix billion people on the planet,
Dialogue: 0,0:40:54.84,0:40:58.04,Default,,0000,0000,0000,,that amount of words is about\Nequal to the number of words
Dialogue: 0,0:40:58.04,0:41:01.08,Default,,0000,0000,0000,,that Google has available\Nat any one instant in time.
Dialogue: 0,0:41:03.48,0:41:08.68,Default,,0000,0000,0000,,Google's computers hoover up\Nand file away every document,\Nweb page, and image they can find.
Dialogue: 0,0:41:08.68,0:41:14.64,Default,,0000,0000,0000,,They then hunt for patterns and\Ncorrelations in all this data,
Dialogue: 0,0:41:14.64,0:41:17.76,Default,,0000,0000,0000,,doing statistics on a massive scale.
Dialogue: 0,0:41:17.76,0:41:25.56,Default,,0000,0000,0000,,And, for me, Google has one project\Nthat's particularly exciting -\Nstatistical language translation.
Dialogue: 0,0:41:25.56,0:41:30.88,Default,,0000,0000,0000,,We wanted to provide access\Nto all the web's information,\Nno matter what language you spoke.
Dialogue: 0,0:41:30.88,0:41:33.52,Default,,0000,0000,0000,,There's just so much information\Non the internet,
Dialogue: 0,0:41:33.52,0:41:37.88,Default,,0000,0000,0000,,you couldn't hope to translate it all\Nby hand into every possible language.
Dialogue: 0,0:41:37.88,0:41:41.56,Default,,0000,0000,0000,,We figured we'd have to be able\Nto do machine translation.
Dialogue: 0,0:41:44.28,0:41:47.36,Default,,0000,0000,0000,,In the past, programmers\Ntried to teach their computers
Dialogue: 0,0:41:47.36,0:41:53.32,Default,,0000,0000,0000,,to see each language as a set of\Ngrammatical rules - much like the\Nway languages are taught at school.
Dialogue: 0,0:41:53.32,0:41:58.76,Default,,0000,0000,0000,,But this didn't work because no set\Nof rules could capture a language
Dialogue: 0,0:41:58.76,0:42:01.48,Default,,0000,0000,0000,,in all its subtlety and ambiguity.
Dialogue: 0,0:42:01.48,0:42:05.84,Default,,0000,0000,0000,,"Having eaten our lunch\Nthe coach departed."
Dialogue: 0,0:42:05.84,0:42:07.92,Default,,0000,0000,0000,,Well, that's obviously incorrect.
Dialogue: 0,0:42:07.92,0:42:12.00,Default,,0000,0000,0000,,Written like that it would imply\Nthat the coach has eaten the lunch.
Dialogue: 0,0:42:12.00,0:42:15.16,Default,,0000,0000,0000,,It would be far better to say...
Dialogue: 0,0:42:15.16,0:42:19.92,Default,,0000,0000,0000,,"having eaten our lunch\Nwe departed in the coach."
Dialogue: 0,0:42:19.92,0:42:26.32,Default,,0000,0000,0000,,Those rules are helpful and they are\Nuseful most of time, but they don't\Nturn out to be true all the time.
Dialogue: 0,0:42:26.32,0:42:30.32,Default,,0000,0000,0000,,And the insight of using statistical\Nmachine translation is saying,
Dialogue: 0,0:42:30.32,0:42:35.28,Default,,0000,0000,0000,,"If you've got to have all these\Nexceptions anyways, maybe you can get\Nby without having any of the rules.
Dialogue: 0,0:42:35.28,0:42:39.48,Default,,0000,0000,0000,,"Maybe you can treat everything\Nas an exception." And that's\Nessentially what we've done.
Dialogue: 0,0:42:48.84,0:42:52.64,Default,,0000,0000,0000,,What the computer is doing when\Nhe's learning how to translate
Dialogue: 0,0:42:52.64,0:42:55.16,Default,,0000,0000,0000,,is to learn correlations\Nbetween words
Dialogue: 0,0:42:55.16,0:42:57.24,Default,,0000,0000,0000,,and correlations between phrases.
Dialogue: 0,0:42:57.24,0:43:00.84,Default,,0000,0000,0000,,So we feed the system very large\Namounts of data
Dialogue: 0,0:43:00.84,0:43:04.72,Default,,0000,0000,0000,,and then the system is seeing that\Na certain word or a certain phrase
Dialogue: 0,0:43:04.72,0:43:07.60,Default,,0000,0000,0000,,correlates very often\Nto the other language.
Dialogue: 0,0:43:09.80,0:43:15.80,Default,,0000,0000,0000,,Google's website currently\Noffers translation between\Nany of 57 different languages.
Dialogue: 0,0:43:15.80,0:43:22.68,Default,,0000,0000,0000,,It does this purely statistically,\Nhaving correlated a huge collection\Nof multilingual texts.
Dialogue: 0,0:43:22.68,0:43:25.60,Default,,0000,0000,0000,,The people that built the system\Ndon't need to know Chinese
Dialogue: 0,0:43:25.60,0:43:29.80,Default,,0000,0000,0000,,in order to build the\NChinese-to-English system,\Nor they don't need to know Arabic.
Dialogue: 0,0:43:29.80,0:43:33.04,Default,,0000,0000,0000,,But the expertise that's needed is\Nbasically knowledge of statistics,
Dialogue: 0,0:43:33.04,0:43:35.84,Default,,0000,0000,0000,,knowledge of computer science,\Nknowledge of infrastructure
Dialogue: 0,0:43:35.84,0:43:40.88,Default,,0000,0000,0000,,to build those very large\Ncomputational systems\Nthat we are building for doing that.
Dialogue: 0,0:43:42.88,0:43:48.36,Default,,0000,0000,0000,,I hooked up with Google\Nfrom my office in Stockholm\Nto try the translator for myself.
Dialogue: 0,0:43:48.36,0:43:51.76,Default,,0000,0000,0000,,'I will type...\Nsome Swedish sentences.'
Dialogue: 0,0:43:51.76,0:43:53.08,Default,,0000,0000,0000,,OK.
Dialogue: 0,0:43:53.08,0:43:55.24,Default,,0000,0000,0000,,Sveriges...
Dialogue: 0,0:43:55.24,0:43:59.28,Default,,0000,0000,0000,,..guldring i orat.
Dialogue: 0,0:44:00.92,0:44:07.40,Default,,0000,0000,0000,,OK. So it says, "Sweden's finance\Nminister has a ponytail\Nand a gold ring in your ear."
Dialogue: 0,0:44:07.40,0:44:11.52,Default,,0000,0000,0000,,I guess it probably means\Nin his ear. 'That's exactly\Ncorrect, it's amazing!
Dialogue: 0,0:44:11.52,0:44:15.40,Default,,0000,0000,0000,,'He comes from the Conservative\Nparty, that's the kind\Nof Sweden we have today.
Dialogue: 0,0:44:15.40,0:44:18.52,Default,,0000,0000,0000,,'I will type one more sentence.'
Dialogue: 0,0:44:18.52,0:44:22.08,Default,,0000,0000,0000,,'I sitt samkonade...'
Dialogue: 0,0:44:22.08,0:44:25.60,Default,,0000,0000,0000,,partnerskap...
Dialogue: 0,0:44:25.60,0:44:28.28,Default,,0000,0000,0000,,nya biskop.
Dialogue: 0,0:44:28.28,0:44:35.20,Default,,0000,0000,0000,,"In his same-sex partnership\Nhas Stockholm's new bishop\Nand his partners a three-year son."
Dialogue: 0,0:44:35.20,0:44:38.12,Default,,0000,0000,0000,,It's almost perfect,\Nthere's one important thing -
Dialogue: 0,0:44:38.12,0:44:41.80,Default,,0000,0000,0000,,it's HER,\Nit's a lesbian partnership.
Dialogue: 0,0:44:41.80,0:44:46.76,Default,,0000,0000,0000,,OK, so those kinds of words his\Nand her are one of the challenges
Dialogue: 0,0:44:46.76,0:44:49.08,Default,,0000,0000,0000,,in translation\Nto get really those right.
Dialogue: 0,0:44:49.08,0:44:51.92,Default,,0000,0000,0000,,Especially when it comes\Nto bishops one can excuse it!
Dialogue: 0,0:44:51.92,0:44:53.64,Default,,0000,0000,0000,,'Right, right.'
Dialogue: 0,0:44:53.64,0:44:58.52,Default,,0000,0000,0000,,I guess more often than not\Nit would probably be a "his".\N'I will write one more sentence.'
Dialogue: 0,0:44:58.52,0:45:01.72,Default,,0000,0000,0000,,Nar Sverige deltar\NI olympiader ar malet
Dialogue: 0,0:45:01.72,0:45:03.72,Default,,0000,0000,0000,,'inte att vinna\Nutan att sla Norge.'
Dialogue: 0,0:45:06.40,0:45:11.96,Default,,0000,0000,0000,,OK. "When Sweden is taking part\Nin Olympic goal is not\Nto win but to beat Norway."
Dialogue: 0,0:45:11.96,0:45:13.64,Default,,0000,0000,0000,,'Yes! This is what it is!
Dialogue: 0,0:45:13.64,0:45:17.92,Default,,0000,0000,0000,,'But they are very good\Nin Winter Olympics, so we\Ncan't make it, but we are trying.'
Dialogue: 0,0:45:17.92,0:45:19.96,Default,,0000,0000,0000,,Ah, very good, very good.
Dialogue: 0,0:45:19.96,0:45:24.96,Default,,0000,0000,0000,,'This is absolutely amazing, you\Nknow, and I was especially impressed
Dialogue: 0,0:45:24.96,0:45:30.52,Default,,0000,0000,0000,,'that it picks up words like\N"same-sex partnership"\Nwhich are very new to the language."
Dialogue: 0,0:45:30.52,0:45:36.92,Default,,0000,0000,0000,,'The translator is good, but\Nif they succeed with what's next,\Nthat'll be remarkable.'
Dialogue: 0,0:45:36.92,0:45:38.44,Default,,0000,0000,0000,,One of the exciting possibilities
Dialogue: 0,0:45:38.44,0:45:42.72,Default,,0000,0000,0000,,is combining the machine\Ntranslation technology with\Nthe speech recognition technology.
Dialogue: 0,0:45:42.72,0:45:45.48,Default,,0000,0000,0000,,Now, both of these\Nare statistical in nature.
Dialogue: 0,0:45:45.48,0:45:51.36,Default,,0000,0000,0000,,The machine translation relies\Non the statistics of mapping\Nfrom one language to another,
Dialogue: 0,0:45:51.36,0:45:57.84,Default,,0000,0000,0000,,and similarly speech recognition\Nrelies on the statistics of mapping\Nfrom a sound form to the words.
Dialogue: 0,0:45:57.84,0:45:59.52,Default,,0000,0000,0000,,When we put them together,
Dialogue: 0,0:45:59.52,0:46:03.20,Default,,0000,0000,0000,,now we have the capability\Nof having instant conversation
Dialogue: 0,0:46:03.20,0:46:06.76,Default,,0000,0000,0000,,between two people\Nthat don't speak a common language.
Dialogue: 0,0:46:06.76,0:46:08.68,Default,,0000,0000,0000,,I can talk to you in my language,
Dialogue: 0,0:46:08.68,0:46:11.88,Default,,0000,0000,0000,,you hear me in your language\Nand you can answer back.
Dialogue: 0,0:46:11.88,0:46:15.00,Default,,0000,0000,0000,,And in real time we can\Nmake that translation,
Dialogue: 0,0:46:15.00,0:46:18.80,Default,,0000,0000,0000,,we can bring two people together\Nand allow them to speak.
Dialogue: 0,0:46:31.40,0:46:39.04,Default,,0000,0000,0000,,The internet is just one\Nof many technologies created\Nto gather massive amounts of data.
Dialogue: 0,0:46:39.04,0:46:43.64,Default,,0000,0000,0000,,Scientists studying\Nour earth and our environment
Dialogue: 0,0:46:43.64,0:46:47.44,Default,,0000,0000,0000,,now use an incredible range\Nof instruments
Dialogue: 0,0:46:47.44,0:46:50.92,Default,,0000,0000,0000,,to measure the processes\Nof our planet.
Dialogue: 0,0:46:52.76,0:47:00.36,Default,,0000,0000,0000,,All around us are sensors\Ncontinuously measuring temperature,\Nwater flow, and ocean currents.
Dialogue: 0,0:47:00.36,0:47:06.80,Default,,0000,0000,0000,,And high in orbit are satellites\Nbusy imaging cloud formations,\Nforest growth and snow cover.
Dialogue: 0,0:47:06.80,0:47:11.36,Default,,0000,0000,0000,,Scientists speak\Nof "instrumenting the earth".
Dialogue: 0,0:47:13.32,0:47:20.16,Default,,0000,0000,0000,,And pointing up to the skies\Nabove are powerful new telescopes\Nmapping the universe.
Dialogue: 0,0:47:30.28,0:47:34.76,Default,,0000,0000,0000,,What's happening in astronomy\Nis typical of how profoundly
Dialogue: 0,0:47:34.76,0:47:39.76,Default,,0000,0000,0000,,this new torrent of data\Nis transforming science.
Dialogue: 0,0:47:39.76,0:47:45.28,Default,,0000,0000,0000,,Astronomers are now addressing many\Nenduring mysteries of the cosmos
Dialogue: 0,0:47:45.28,0:47:49.60,Default,,0000,0000,0000,,by applying statistical methods\Nto all this new data.
Dialogue: 0,0:47:59.80,0:48:03.36,Default,,0000,0000,0000,,The galaxy is a very big place and\Nit's got billions of stars in it,
Dialogue: 0,0:48:03.36,0:48:09.40,Default,,0000,0000,0000,,and so to put together a coherent\Npicture of the whole galaxy requires\Nhaving an enormous amount of data.
Dialogue: 0,0:48:09.40,0:48:13.72,Default,,0000,0000,0000,,And before you could do\Na large sky survey with\Nsensitive, digital detectors
Dialogue: 0,0:48:13.72,0:48:16.88,Default,,0000,0000,0000,,that meant that you could map many,\Nmany stars all at once,
Dialogue: 0,0:48:16.88,0:48:20.68,Default,,0000,0000,0000,,it was very difficult to build up\Nenough data on enough of the galaxy.
Dialogue: 0,0:48:24.60,0:48:28.56,Default,,0000,0000,0000,,In the past, large surveys\Nof the night sky had to be done
Dialogue: 0,0:48:28.56,0:48:32.40,Default,,0000,0000,0000,,by exposing thousands\Nof large photographic plates.
Dialogue: 0,0:48:32.40,0:48:37.20,Default,,0000,0000,0000,,But these surveys could take\N25 years or more to complete.
Dialogue: 0,0:48:39.04,0:48:44.68,Default,,0000,0000,0000,,Then, in the 1990s, came digital\Nastronomy and a huge increase
Dialogue: 0,0:48:44.68,0:48:49.60,Default,,0000,0000,0000,,in both the amount\Nand the accessibility of data.
Dialogue: 0,0:48:49.60,0:48:55.96,Default,,0000,0000,0000,,The Sloan Sky Survey\Nis the world's biggest yet,\Nusing a massive digital sensor
Dialogue: 0,0:48:55.96,0:49:00.84,Default,,0000,0000,0000,,mounted on the back\Nof a custom-built telescope\Nin New Mexico.
Dialogue: 0,0:49:00.84,0:49:05.24,Default,,0000,0000,0000,,It's scanned the sky night\Nafter night for eight years,
Dialogue: 0,0:49:05.24,0:49:09.80,Default,,0000,0000,0000,,building up a composite picture\Nin unprecedented resolution.
Dialogue: 0,0:49:09.80,0:49:14.84,Default,,0000,0000,0000,,The Sloan is some of the best,\Ndeepest survey data\Nthat we have in astronomy.
Dialogue: 0,0:49:14.84,0:49:18.76,Default,,0000,0000,0000,,Both on our own galaxy and\Non galaxies further away from ours.
Dialogue: 0,0:49:24.08,0:49:27.32,Default,,0000,0000,0000,,All the Sloan data\Nis on the internet,
Dialogue: 0,0:49:27.32,0:49:34.12,Default,,0000,0000,0000,,and with it astronomers\Nhave identified millions of hitherto\Nunknown stars and galaxies.
Dialogue: 0,0:49:34.12,0:49:37.48,Default,,0000,0000,0000,,They also comb the database\Nfor statistical patterns
Dialogue: 0,0:49:37.48,0:49:42.80,Default,,0000,0000,0000,,which will prove, disprove,\Nor even suggest new theories.
Dialogue: 0,0:49:42.80,0:49:49.16,Default,,0000,0000,0000,,So we have this idea that galaxies\Ngrow, they become large galaxies like\Nthe one we live in, the milky way,
Dialogue: 0,0:49:49.16,0:49:55.88,Default,,0000,0000,0000,,not all at once, or not smoothly,\Nbut by continuously incorporating,
Dialogue: 0,0:49:55.88,0:49:59.16,Default,,0000,0000,0000,,basically cannibalising,\Nsmaller galaxies.
Dialogue: 0,0:49:59.16,0:50:04.00,Default,,0000,0000,0000,,They dissolve them\Nand they become part\Nof the bigger galaxy as it grows.
Dialogue: 0,0:50:06.04,0:50:12.52,Default,,0000,0000,0000,,It's a startling idea,\Nand, in the Sloan data,\Nis the evidence to support it.
Dialogue: 0,0:50:12.52,0:50:16.28,Default,,0000,0000,0000,,Groups of stars that came\Nfrom cannibalised galaxies
Dialogue: 0,0:50:16.28,0:50:21.24,Default,,0000,0000,0000,,stand out in the Sloan data\Nas statistically different\Nfrom other stars
Dialogue: 0,0:50:21.24,0:50:24.28,Default,,0000,0000,0000,,because they move\Nat a different velocity.
Dialogue: 0,0:50:24.28,0:50:28.68,Default,,0000,0000,0000,,Each big spike\Non one of these distribution graphs
Dialogue: 0,0:50:28.68,0:50:35.12,Default,,0000,0000,0000,,means Professor Rockosi has found\Na group of stars all travelling\Nin a different way to the rest.
Dialogue: 0,0:50:35.12,0:50:38.36,Default,,0000,0000,0000,,They are the telltale\Npatterns she's looking for.
Dialogue: 0,0:50:40.24,0:50:44.96,Default,,0000,0000,0000,,The evidence is accumulating\Nthat, in fact, this really is\Nhow galaxies grow,
Dialogue: 0,0:50:44.96,0:50:47.44,Default,,0000,0000,0000,,or an important way\Nin which how galaxies grow.
Dialogue: 0,0:50:47.44,0:50:53.00,Default,,0000,0000,0000,,And so this is an important part\Nof understanding how galaxies form,\Nnot only ours but every galaxy.
Dialogue: 0,0:50:56.36,0:51:00.40,Default,,0000,0000,0000,,The more data there is,\Nthe more discoveries can be made.
Dialogue: 0,0:51:00.40,0:51:03.32,Default,,0000,0000,0000,,And the technology\Nis getting better all the time.
Dialogue: 0,0:51:03.32,0:51:07.56,Default,,0000,0000,0000,,The next big survey telescope\Nstarts its work in 2015.
Dialogue: 0,0:51:07.56,0:51:10.76,Default,,0000,0000,0000,,It will leave Sloan in the dust!
Dialogue: 0,0:51:10.76,0:51:16.16,Default,,0000,0000,0000,,Sloan has taken eight years to cover\None quarter of the night sky.
Dialogue: 0,0:51:17.68,0:51:25.68,Default,,0000,0000,0000,,The new telescope will scan\Nthe entire sky, in even greater\Nresolution, every three days!
Dialogue: 0,0:51:34.12,0:51:41.00,Default,,0000,0000,0000,,The vast amounts of data\Nwe have today allows researchers\Nin all sorts of fields
Dialogue: 0,0:51:41.00,0:51:46.28,Default,,0000,0000,0000,,to test their theories\Non a previously unimaginable scale.
Dialogue: 0,0:51:46.28,0:51:53.60,Default,,0000,0000,0000,,But more than this,\Nit may even change\Nthe fundamental way science is done.
Dialogue: 0,0:51:53.60,0:51:58.56,Default,,0000,0000,0000,,With the power of today's computers\Napplied to all this data,
Dialogue: 0,0:51:58.56,0:52:03.88,Default,,0000,0000,0000,,the machines might even be able\Nto guide the researchers.
Dialogue: 0,0:52:14.60,0:52:17.92,Default,,0000,0000,0000,,We're at a potentially\Nprofoundly important
Dialogue: 0,0:52:17.92,0:52:22.56,Default,,0000,0000,0000,,and potentially one of the most\Nsignificant points in science,
Dialogue: 0,0:52:22.56,0:52:24.68,Default,,0000,0000,0000,,and certainly one of\Nthe most exciting,
Dialogue: 0,0:52:24.68,0:52:32.08,Default,,0000,0000,0000,,where the potential to transform\Nnot just how scientists do science\Nbut even what science is possible.
Dialogue: 0,0:52:32.08,0:52:34.68,Default,,0000,0000,0000,,And what will power\Nthat transformation
Dialogue: 0,0:52:34.68,0:52:38.40,Default,,0000,0000,0000,,of both how science is done\Nand even what science is possible
Dialogue: 0,0:52:38.40,0:52:40.12,Default,,0000,0000,0000,,is going to be computation.
Dialogue: 0,0:52:41.80,0:52:49.44,Default,,0000,0000,0000,,Many of the dynamics of the natural\Nworld, like the interplay between\Nthe rainforests and the atmosphere,
Dialogue: 0,0:52:49.44,0:52:53.56,Default,,0000,0000,0000,,are so complex that we don't\Nas yet really understand them.
Dialogue: 0,0:52:53.56,0:52:59.28,Default,,0000,0000,0000,,But now computers are generating\Nliterally tens of thousands\Nof different simulations
Dialogue: 0,0:52:59.28,0:53:03.48,Default,,0000,0000,0000,,of how these\Nbiological systems might work.
Dialogue: 0,0:53:03.48,0:53:07.84,Default,,0000,0000,0000,,It's like creating thousands\Nof hypothetical parallel worlds.
Dialogue: 0,0:53:07.84,0:53:10.64,Default,,0000,0000,0000,,Each and every one\Nof these simulations
Dialogue: 0,0:53:10.64,0:53:18.36,Default,,0000,0000,0000,,is analysed with statistics\Nto see if any are a good match\Nfor what is observed in nature.
Dialogue: 0,0:53:18.36,0:53:21.84,Default,,0000,0000,0000,,The computers can now\Nautomatically generate,
Dialogue: 0,0:53:21.84,0:53:26.24,Default,,0000,0000,0000,,test and discard hypotheses\Nwith scarcely a human in sight.
Dialogue: 0,0:53:28.24,0:53:35.12,Default,,0000,0000,0000,,This new application of statistics\Nwill become absolutely vital\Nfor the future of science.
Dialogue: 0,0:53:35.12,0:53:39.40,Default,,0000,0000,0000,,It's creating a new paradigm,\Nif you like,
Dialogue: 0,0:53:39.40,0:53:42.64,Default,,0000,0000,0000,,in science, in the way\Nin which we can do science,
Dialogue: 0,0:53:42.64,0:53:45.28,Default,,0000,0000,0000,,which is increasingly...
Dialogue: 0,0:53:45.28,0:53:51.16,Default,,0000,0000,0000,,Which one might characterise as...\Ndata-centric or data driven
Dialogue: 0,0:53:51.16,0:53:55.00,Default,,0000,0000,0000,,rather than being hypothesis-driven\Nor experimentally-driven.
Dialogue: 0,0:53:55.00,0:53:58.24,Default,,0000,0000,0000,,So, it's exciting times\Nin terms of the science,
Dialogue: 0,0:53:58.24,0:54:02.20,Default,,0000,0000,0000,,in terms of the computation\Nand in terms of the statistics.
Dialogue: 0,0:54:08.80,0:54:15.48,Default,,0000,0000,0000,,Now, if all that sounds a bit\Nabstract and theoretical to you,\Nhow about one final frontier?
Dialogue: 0,0:54:15.48,0:54:19.04,Default,,0000,0000,0000,,Could statistics even make\Nsense of your feelings?
Dialogue: 0,0:54:21.20,0:54:25.80,Default,,0000,0000,0000,,In California - where else? -\None computer scientist
Dialogue: 0,0:54:25.80,0:54:32.68,Default,,0000,0000,0000,,is harvesting the internet to try\Nto divine the patterns of our\Ninnermost thoughts and emotions.
Dialogue: 0,0:54:44.80,0:54:46.36,Default,,0000,0000,0000,,This is the madness movement.
Dialogue: 0,0:54:46.36,0:54:50.96,Default,,0000,0000,0000,,The madness movement represents\Na skyscraper view of the world.
Dialogue: 0,0:54:50.96,0:54:54.88,Default,,0000,0000,0000,,Each of these brightly coloured dots\Nis an individual feeling
Dialogue: 0,0:54:54.88,0:54:58.72,Default,,0000,0000,0000,,expressed by someone out there\Nin a blog or a tweet.
Dialogue: 0,0:54:58.72,0:55:04.48,Default,,0000,0000,0000,,And when you click on the dot\Nit explodes to reveal the\Nunderlying feeling of that person.
Dialogue: 0,0:55:04.48,0:55:07.08,Default,,0000,0000,0000,,This is what people say\Nthey're feeling today.
Dialogue: 0,0:55:07.72,0:55:10.16,Default,,0000,0000,0000,,Better...safe...
Dialogue: 0,0:55:10.16,0:55:12.04,Default,,0000,0000,0000,,crappy...
Dialogue: 0,0:55:12.04,0:55:14.56,Default,,0000,0000,0000,,well...
Dialogue: 0,0:55:14.56,0:55:18.44,Default,,0000,0000,0000,,pretty...special...
Dialogue: 0,0:55:18.44,0:55:20.80,Default,,0000,0000,0000,,sorry...alone...
Dialogue: 0,0:55:25.56,0:55:29.04,Default,,0000,0000,0000,,So, every minute, We Feel Fine\Ncrawls the world's blogs,
Dialogue: 0,0:55:29.04,0:55:34.12,Default,,0000,0000,0000,,takes all the sentences\Nthat start with the words\N"I feel" or "I am feeling",
Dialogue: 0,0:55:34.12,0:55:35.92,Default,,0000,0000,0000,,and puts them in a database.
Dialogue: 0,0:55:35.92,0:55:40.08,Default,,0000,0000,0000,,We collect all the feelings\Nand we count the most common.
Dialogue: 0,0:55:40.08,0:55:43.32,Default,,0000,0000,0000,,They are better...bad...
Dialogue: 0,0:55:43.32,0:55:45.64,Default,,0000,0000,0000,,good...right...
Dialogue: 0,0:55:45.64,0:55:48.52,Default,,0000,0000,0000,,guilty...sick...
Dialogue: 0,0:55:48.52,0:55:51.68,Default,,0000,0000,0000,,the same...like shit...
Dialogue: 0,0:55:51.68,0:55:54.72,Default,,0000,0000,0000,,sorry...well...
Dialogue: 0,0:55:54.72,0:55:56.24,Default,,0000,0000,0000,,and so on.
Dialogue: 0,0:55:58.32,0:56:01.76,Default,,0000,0000,0000,,And we can take a look at any\None feeling and analyse it.
Dialogue: 0,0:56:01.76,0:56:04.80,Default,,0000,0000,0000,,Right now a lot of people\Nare feeling happy.
Dialogue: 0,0:56:04.80,0:56:11.32,Default,,0000,0000,0000,,We can take a look at all the\Npeople who are happy and break it\Ndown by age, gender or location.
Dialogue: 0,0:56:11.32,0:56:16.84,Default,,0000,0000,0000,,Since bloggers have public profiles\Nwe have that information and\Nso we can ask questions like,
Dialogue: 0,0:56:16.84,0:56:21.40,Default,,0000,0000,0000,,"Are women happier than men?"\Nor, "Is England happier\Nthan the United States?"
Dialogue: 0,0:56:30.24,0:56:33.12,Default,,0000,0000,0000,,We find that, as people get older,\Nthey get happier.
Dialogue: 0,0:56:33.12,0:56:40.56,Default,,0000,0000,0000,,And, moreover, we find that\Nfor younger people they associate\Nhappiness more with excitement,
Dialogue: 0,0:56:40.56,0:56:47.00,Default,,0000,0000,0000,,and, as people get older,\Nthey associate happiness\Nmore with peacefulness.
Dialogue: 0,0:56:51.24,0:56:57.76,Default,,0000,0000,0000,,And we also find that women feel\Nloved more often than men,\Nbut also more guilty.
Dialogue: 0,0:56:57.76,0:57:02.48,Default,,0000,0000,0000,,While men feel good more often\Nthan women, but also more alone.
Dialogue: 0,0:57:06.64,0:57:12.48,Default,,0000,0000,0000,,As people lead more and\Nmore of their lives online,\Nthey leave behind digital traces,
Dialogue: 0,0:57:12.48,0:57:19.84,Default,,0000,0000,0000,,and with these digital traces\Nwe can begin to statistically analyse\Nwhat it means to be human.
Dialogue: 0,0:57:51.28,0:57:54.48,Default,,0000,0000,0000,,So where does all of this leave us?
Dialogue: 0,0:57:54.48,0:58:00.16,Default,,0000,0000,0000,,We generate unimaginable\Nquantities of data\Nabout everything you can think of.
Dialogue: 0,0:58:00.16,0:58:02.80,Default,,0000,0000,0000,,We analyse it to reveal\Nthe patterns.
Dialogue: 0,0:58:02.80,0:58:10.48,Default,,0000,0000,0000,,And now not only experts\Nbut all of us can understand\Nthe stories in the numbers.
Dialogue: 0,0:58:18.16,0:58:21.08,Default,,0000,0000,0000,,Instead of being\Nled astray by prejudice,
Dialogue: 0,0:58:21.08,0:58:28.16,Default,,0000,0000,0000,,with statistics at our fingertips,\Nour eyes can be open\Nfor a fact-based view of the world.
Dialogue: 0,0:58:28.16,0:58:33.76,Default,,0000,0000,0000,,So, more than ever before, we can\Nbecome authors of our own destiny.
Dialogue: 0,0:58:33.76,0:58:36.80,Default,,0000,0000,0000,,And that's pretty\Nexciting isn't it?!
Dialogue: 0,0:58:37.68,0:58:44.20,Default,,0000,0000,0000,,# 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,\N12, 13, 14, 15, 16, 17, 18, 19, 20
Dialogue: 0,0:58:44.20,0:58:50.80,Default,,0000,0000,0000,,# 1, 22, 3, 24, 25, 26, 27, 28, 9,\N30, 31, 32, 3, 34, 35, 36, 7
Dialogue: 0,0:58:50.80,0:58:54.44,Default,,0000,0000,0000,,# 38, 39, 40, 41, 42, 3,\N44, 45, 46, 47
Dialogue: 0,0:58:54.44,0:58:58.68,Default,,0000,0000,0000,,LYRICS DEGENERATE INTO GIBBERISH
Dialogue: 0,0:59:08.68,0:59:13.40,Default,,0000,0000,0000,,GIBBERISH DEGENERATES INTO NOISE
Dialogue: 0,0:59:13.40,0:59:14.44,Default,,0000,0000,0000,,# 100. #