The Mathematics of Love | Hannah Fry | TEDxBinghamtonUniversity
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0:16 - 0:21Today I want to talk to youabout the mathematics of love.
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0:21 - 0:23Now, I think that we can all agree
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0:23 - 0:28that mathematiciansare famously excellent at finding love.
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0:28 - 0:31But it's not justbecause of our dashing personalities,
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0:31 - 0:36superior conversational skillsand excellent pencil cases.
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0:36 - 0:40It's also because we've actually donean awful lot of work into the maths
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0:40 - 0:42of how to find the perfect partner.
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0:42 - 0:46Now, in my favorite paperon the subject, which is entitled,
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0:46 - 0:49"Why I Don't Have a Girlfriend" --(Laughter) --
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0:49 - 0:53Peter Backus tries to ratehis chances of finding love.
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0:53 - 0:55Now, Peter's not a very greedy man.
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0:55 - 0:58Of all of the available women in the U.K.,
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0:58 - 1:01all Peter's looking foris somebody who lives near him,
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1:01 - 1:03somebody in the right age range,
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1:03 - 1:06somebody with a university degree,
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1:06 - 1:08somebody he's likely to get on well with,
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1:08 - 1:10somebody who's likely to be attractive,
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1:10 - 1:12somebody who's likely to find him attractive.
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1:12 - 1:15(Laughter)
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1:15 - 1:20And comes up with an estimateof 26 women in the whole of the UK.
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1:21 - 1:24It's not looking very good, is it Peter?
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1:24 - 1:25Now, just to put that into perspective,
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1:25 - 1:29that's about 400 times fewerthan the best estimates
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1:29 - 1:33of how many intelligentextraterrestrial life forms there are.
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1:33 - 1:38And it also gives Petera 1 in 285,000 chance
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1:38 - 1:40of bumping into any oneof these special ladies
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1:40 - 1:41on a given night out.
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1:41 - 1:43I'd like to thinkthat's why mathematicians
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1:43 - 1:47don't really bothergoing on nights out anymore.
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1:47 - 1:49The thing is that I personally
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1:49 - 1:51don't subscribeto such a pessimistic view.
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1:51 - 1:54Because I know,just as well as all of you do,
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1:54 - 1:56that love doesn't really work like that.
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1:56 - 2:01Human emotion isn't neatly orderedand rational and easily predictable.
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2:01 - 2:04But I also know that that doesn't mean
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2:04 - 2:07that mathematics hasn't got somethingthat it can offer us
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2:07 - 2:11because, love, as with most of life,is full of patterns
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2:11 - 2:15and mathematics is, ultimately,all about the study of patterns.
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2:15 - 2:19Patterns from predicting the weatherto the fluctuations in the stock market,
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2:19 - 2:23to the movement of the planetsor the growth of cities.
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2:23 - 2:25And if we're being honest,none of those things
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2:25 - 2:29are exactly neatly orderedand easily predictable, either.
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2:29 - 2:34Because I believe that mathematicsis so powerful that it has the potential
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2:34 - 2:38to offer us a new way of lookingat almost anything.
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2:38 - 2:41Even something as mysterious as love.
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2:41 - 2:43And so, to try to persuade you
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2:43 - 2:47of how totally amazing, excellentand relevant mathematics is,
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2:47 - 2:55I want to give you my top threemathematically verifiable tips for love.
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2:56 - 2:58Okay, so Top Tip #1:
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2:58 - 3:01How to win at online dating.
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3:02 - 3:06So my favorite online dating website is OkCupid,
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3:06 - 3:10not least because it was startedby a group of mathematicians.
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3:10 - 3:11Now, because they're mathematicians,
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3:11 - 3:13they have been collecting data
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3:13 - 3:16on everybody who uses their sitefor almost a decade.
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3:16 - 3:18And they've been trying to search for patterns
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3:18 - 3:20in the way that we talk about ourselves
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3:20 - 3:22and the way that we interact with each other
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3:22 - 3:24on an online dating website.
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3:24 - 3:27And they've come up with someseriously interesting findings.
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3:27 - 3:28But my particular favorite
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3:28 - 3:32is that it turns outthat on an online dating website,
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3:32 - 3:38how attractive you aredoes not dictate how popular you are,
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3:38 - 3:41and actually, having peoplethink that you're ugly
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3:41 - 3:44can work to your advantage.
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3:44 - 3:46Let me show you how this works.
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3:46 - 3:51In a thankfully voluntarysection of OkCupid,
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3:51 - 3:54you are allowed to ratehow attractive you think people are
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3:54 - 3:56on a scale between 1 and 5.
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3:56 - 3:59Now, if we compare this score, the average score,
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3:59 - 4:02to how many messages aselection of people receive,
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4:02 - 4:04you can begin to get a sense
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4:04 - 4:08of how attractiveness links to popularityon an online dating website.
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4:08 - 4:11This is the graph that the OkCupid guyshave come up with.
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4:11 - 4:14And the important thing to noticeis that it's not totally true
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4:14 - 4:17that the more attractive you are,the more messages you get.
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4:17 - 4:21But the question arises thenof what is it about people up here
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4:21 - 4:26who are so much more popularthan people down here,
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4:26 - 4:28even though they have thesame score of attractiveness?
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4:28 - 4:33And the reason why is that it's not just straightforward looks that are important.
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4:33 - 4:35So let me try to illustrate theirfindings with an example.
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4:35 - 4:40So if you take someone likePortia de Rossi, for example,
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4:40 - 4:44everybody agrees that Portia de Rossiis a very beautiful woman.
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4:44 - 4:48Nobody thinks that she's ugly,but she's not a supermodel, either.
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4:48 - 4:53If you compare Portia de Rossito someone like Sarah Jessica Parker,
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4:53 - 4:56now, a lot of people, myself included, I should say,
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4:56 - 5:00think that Sarah Jessica Parkeris seriously fabulous
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5:00 - 5:03and possibly one of themost beautiful creatures
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5:03 - 5:06to have ever have walked on the face of the Earth.
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5:06 - 5:12But some other people, i.e., most of the Internet,
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5:12 - 5:18seem to think that she looks a bit like a horse. (Laughter)
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5:18 - 5:21Now, I think that if you ask peoplehow attractive they thought
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5:21 - 5:23Sarah Jessica Parker or Portia de Rossi were,
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5:23 - 5:26and you ask them to give them a score between 1 and 5,
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5:26 - 5:29I reckon that they'd average outto have roughly the same score.
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5:29 - 5:32But the way that people would votewould be very different.
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5:32 - 5:35So Portia's scores wouldall be clustered around the 4
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5:35 - 5:37because everybody agrees that she's very beautiful,
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5:37 - 5:40whereas Sarah Jessica Parkercompletely divides opinion.
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5:40 - 5:42There'd be a huge spread in her scores.
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5:42 - 5:44And actually it's this spread that counts.
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5:44 - 5:47It's this spreadthat makes you more popular
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5:47 - 5:49on an online Internet dating website.
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5:49 - 5:50So what that means then
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5:50 - 5:53is that if some peoplethink that you're attractive,
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5:53 - 5:55you're actually better off
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5:55 - 6:00having some other peoplethink that you're a massive minger.
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6:00 - 6:02That's much betterthan everybody just thinking
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6:02 - 6:04that you're the cute girl next door.
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6:04 - 6:06Now, I think this begins makes a bit more sense
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6:06 - 6:09when you think in terms of the peoplewho are sending these messages.
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6:09 - 6:12So let's say that you thinksomebody's attractive,
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6:12 - 6:16but you suspect that other peoplewon't necessarily be that interested.
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6:16 - 6:19That means there'sless competition for you
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6:19 - 6:21and it's an extra incentivefor you to get in touch.
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6:21 - 6:24Whereas compare that to if you think somebody is attractive
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6:24 - 6:27but you suspect that everybody is going to think they're attractive.
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6:27 - 6:31Well, why would you bother humiliating yourself, let's be honest?
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6:31 - 6:33Here's where the reallyinteresting part comes.
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6:33 - 6:37Because when people choose the picturesthat they use on an online dating website,
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6:37 - 6:40they often try to minimize the things
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6:40 - 6:43that they think some people will find unattractive.
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6:43 - 6:47The classic example is peoplewho are, perhaps, a little bit overweight
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6:47 - 6:51deliberately choosing a very cropped photo,
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6:51 - 6:53or bald men, for example,
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6:53 - 6:55deliberately choosing pictureswhere they're wearing hats.
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6:55 - 6:58But actually this is the opposite of what you should do
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6:58 - 7:00if you want to be successful.
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7:00 - 7:04You should really, instead, play up to whatever it is that makes you different,
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7:04 - 7:08even if you think that some peoplewill find it unattractive.
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7:08 - 7:12Because the people who fancy youare just going to fancy you anyway,
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7:12 - 7:16and the unimportant losers who don't,well, they only play up to your advantage.
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7:16 - 7:19Okay, Top Tip #2:How to pick the perfect partner.
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7:19 - 7:22So let's imagine thenthat you're a roaring success
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7:22 - 7:23on the dating scene.
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7:23 - 7:27But the question arises of how do you then convert that success
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7:27 - 7:31into longer-term happinessand in particular,
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7:31 - 7:35how do you decidewhen is the right time to settle down?
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7:35 - 7:38Now generally,it's not advisable to just cash in
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7:38 - 7:40and marry the first personwho comes along
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7:40 - 7:43and shows you any interest at all.
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7:43 - 7:46But, equally, you don't really want to leave it too long
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7:46 - 7:49if you want to maximize your chance of long-term happiness.
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7:49 - 7:52As my favorite author, Jane Austen, puts it,
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7:52 - 7:54"An unmarried woman of seven and twenty
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7:54 - 7:58can never hope to feel orinspire affection again."
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7:58 - 8:00(Laughter)
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8:00 - 8:03Thanks a lot, Jane.What do you know about love?
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8:04 - 8:05So the question is then,
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8:05 - 8:08how do you know when is the right time to settle down
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8:08 - 8:11given all the people that you can date in your lifetime?
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8:11 - 8:14Thankfully, there's a rather delicious bitof mathematics that we can use
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8:14 - 8:17to help us out here, calledoptimal stopping theory.
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8:17 - 8:19So let's imagine then,
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8:19 - 8:21that you start dating when you're 15
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8:21 - 8:25and ideally, you'd like to be marriedby the time that you're 35.
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8:25 - 8:27And there's a number of people
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8:27 - 8:29that you could potentiallydate across your lifetime,
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8:29 - 8:31and they'll be at varying levels of goodness.
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8:31 - 8:34Now the rules are that once you cash in and get married,
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8:34 - 8:37you can't look ahead to seewhat you could have had,
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8:37 - 8:40and equally, you can't go backand change your mind.
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8:40 - 8:41In my experience at least,
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8:41 - 8:44I find that typically people don'tmuch like being recalled
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8:44 - 8:49years after being passed up for somebody else, or that's just me.
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8:49 - 8:53So the math says thenthat what you should do
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8:53 - 8:56in the first 37 percent of your dating window,
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8:56 - 9:00you should just reject everybodyas serious marriage potential.
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9:00 - 9:02(Laughter)
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9:02 - 9:05And then, you should pick the next person that comes along
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9:05 - 9:08that is better than everybody that you've seen before.
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9:08 - 9:09So here's the example.
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9:09 - 9:12Now if you do this, it can bemathematically proven, in fact,
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9:12 - 9:15that this is the best possible way
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9:15 - 9:19of maximizing your chances of finding the perfect partner.
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9:19 - 9:24Now unfortunately, I have to tell you thatthis method does come with some risks.
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9:24 - 9:29For instance, imagine if your perfect partner appeared
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9:29 - 9:32during your first 37 percent.
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9:32 - 9:35Now, unfortunately, you'd have to reject them.
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9:35 - 9:38(Laughter)
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9:38 - 9:40Now, if you're following the maths,
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9:40 - 9:42I'm afraid no one else comes along
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9:42 - 9:44that's better than anyoneyou've seen before,
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9:44 - 9:48so you have to go on rejecting everyone and die alone.
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9:48 - 9:50(Laughter)
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9:51 - 9:56Probably surrounded by catsnibbling at your remains.
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9:56 - 9:59Okay, another risk is, let's imagine, instead,
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9:59 - 10:03that the first people that you datedin your first 37 percent
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10:03 - 10:07are just incredibly dull,boring, terrible people.
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10:07 - 10:09Now, that's okay, because you're in your rejection phase,
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10:09 - 10:11so thats fine, you can reject them.
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10:11 - 10:15But then imagine, the nextperson to come along
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10:15 - 10:19is just marginally less boring, dull and terrible
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10:19 - 10:21than everybody that you've seen before.
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10:21 - 10:25Now, if you are following the maths,I'm afraid you have to marry them
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10:25 - 10:28and end up in a relationshipwhich is, frankly, suboptimal.
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10:28 - 10:29Sorry about that.
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10:29 - 10:32But I do think that there'san opportunity here
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10:32 - 10:35for Hallmark to cash in onand really cater for this market.
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10:35 - 10:37A Valentine's Day card like this.(Laughter)
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10:37 - 10:41"My darling husband, youare marginally less terrible
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10:41 - 10:44than the first 37 percentof people I dated."
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10:44 - 10:49It's actually more romanticthan I normally manage.
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10:49 - 10:54Okay, so this method doesn't giveyou a 100 percent success rate,
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10:54 - 10:57but there's no other possiblestrategy that can do any better.
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10:57 - 11:00And actually, in the wild,there are certain types
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11:00 - 11:04of fish which follow andemploy this exact strategy.
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11:04 - 11:06So they reject every possible suitor that turns up
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11:06 - 11:09in the first 37 percent of the mating season,
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11:09 - 11:13and then they pick the next fishthat comes along after that window
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11:13 - 11:15that's, I don't know, bigger and burlier
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11:15 - 11:18than all of the fish that they've seen before.
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11:18 - 11:22I also think that subconsciously,humans, we do sort of do this anyway.
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11:22 - 11:26We give ourselves a little bit of timeto play the field,
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11:26 - 11:29get a feel for the marketplace or whatever when we're young.
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11:29 - 11:34And then we only start looking seriouslyat potential marriage candidates
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11:34 - 11:36once we hit our mid-to-late 20s.
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11:36 - 11:39I think this is conclusive proof,if ever it were needed,
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11:39 - 11:43that everybody's brains are prewired to be just a little bit mathematical.
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11:44 - 11:45Okay, so that was Top Tip #2.
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11:45 - 11:49Now, Top Tip #3: How to avoid divorce.
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11:49 - 11:52Okay, so let's imagine thenthat you picked your perfect partner
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11:52 - 11:57and you're settling intoa lifelong relationship with them.
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11:57 - 12:01Now, I like to think that everybodywould ideally like to avoid divorce,
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12:01 - 12:05apart from, I don't know, Piers Morgan's wife, maybe?
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12:06 - 12:08But it's a sad fact of modern life
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12:08 - 12:12that 1 in 2 marriages in theStates ends in divorce,
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12:12 - 12:16with the rest of the worldnot being far behind.
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12:16 - 12:18Now, you can be forgiven, perhaps
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12:18 - 12:21for thinking that the argumentsthat precede a marital breakup
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12:21 - 12:25are not an ideal candidatefor mathematical investigation.
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12:25 - 12:27For one thing, it's very hard to know
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12:27 - 12:30what you should be measuring or what you should be quantifying.
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12:30 - 12:36But this didn't stop a psychologist,John Gottman, who did exactly that.
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12:36 - 12:42Gottman observed hundreds of coupleshaving a conversation
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12:42 - 12:44and recorded, well, everything you can think of.
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12:44 - 12:47So he recorded what was said in the conversation,
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12:47 - 12:49he recorded their skin conductivity,
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12:49 - 12:51he recorded their facial expressions,
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12:51 - 12:53their heart rates, their blood pressure,
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12:53 - 12:59basically everything apart from whetheror not the wife was actually always right,
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12:59 - 13:02which incidentally she totally is.
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13:02 - 13:05But what Gottman and his team found
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13:05 - 13:08was that one of themost important predictors
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13:08 - 13:10for whether or not a coupleis going to get divorced
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13:10 - 13:15was how positive or negative each partner was being in the conversation.
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13:15 - 13:18Now, couples that were very low-risk
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13:18 - 13:22scored a lot more positive pointson Gottman's scale than negative.
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13:22 - 13:24Whereas bad relationships,
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13:24 - 13:27by which I mean, probablygoing to get divorced,
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13:27 - 13:31they found themselves getting into a spiral of negativity.
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13:31 - 13:34Now just by using these very simple ideas,
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13:34 - 13:36Gottman and his group were able to predict
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13:36 - 13:39whether a given couplewas going to get divorced
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13:39 - 13:42with a 90 percent accuracy.
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13:42 - 13:45But it wasn't until he teamed upwith a mathematician, James Murray,
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13:45 - 13:47that they really started to understand
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13:47 - 13:52what causes these negativity spirals and how they occur.
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13:52 - 13:53And the results that they found
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13:53 - 13:58I think are just incrediblyimpressively simple and interesting.
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13:58 - 14:02So these equations, they predict how the wife or husband is going to respond
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14:02 - 14:04in their next turn of the conversation,
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14:04 - 14:06how positive or negativethey're going to be.
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14:06 - 14:08And these equations, they depend on
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14:08 - 14:10the mood of the person when they're on their own,
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14:10 - 14:13the mood of the person whenthey're with their partner,
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14:13 - 14:15but most importantly, they depend on
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14:15 - 14:18how much the husband and wifeinfluence one another.
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14:18 - 14:21Now, I think it's important to point out at this stage,
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14:21 - 14:24that these exact equations have also been shown
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14:24 - 14:26to be perfectly able at describing
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14:26 - 14:30what happens between twocountries in an arms race.
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14:30 - 14:32(Laughter)
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14:34 - 14:38So that -- an arguing couplespiraling into negativity
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14:38 - 14:40and teetering on the brink of divorce --
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14:40 - 14:44is actually mathematically equivalent tothe beginning of a nuclear war.
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14:44 - 14:47(Laughter)
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14:47 - 14:49But the really important termin this equation
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14:49 - 14:52is the influence that peoplehave on one another,
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14:52 - 14:55and in particular, something called the negativity threshold.
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14:55 - 14:57Now, the negativity threshold,
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14:57 - 15:01you can think of ashow annoying the husband can be
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15:01 - 15:05before the wife starts to get really pissed off, and vice versa.
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15:05 - 15:10Now, I always thought that good marriageswere about compromise and understanding
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15:10 - 15:13and allowing the person to have the space to be themselves.
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15:13 - 15:17So I would have thought that perhapsthe most successful relationships
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15:17 - 15:20were ones where there wasa really high negativity threshold.
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15:20 - 15:22Where couples let things go
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15:22 - 15:24and only brought things up if they really were a big deal.
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15:24 - 15:28But actually, the mathematicsand subsequent findings by the team
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15:28 - 15:31have shown the exact opposite is true.
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15:31 - 15:34The best couples,or the most successful couples,
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15:34 - 15:38are the ones with a really low negativity threshold.
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15:38 - 15:41These are the couples that don'tlet anything go unnoticed
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15:41 - 15:44and allow each other some room to complain.
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15:44 - 15:50These are the couples that are continuallytrying to repair their own relationship,
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15:50 - 15:52that have a much more positiveoutlook on their marriage.
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15:52 - 15:55Couples that don't let things go
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15:55 - 16:00and couples that don't let trivial thingsend up being a really big deal.
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16:00 - 16:06Now of course, it takes bit more than just a low negativity threshold
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16:06 - 16:10and not compromising tohave a successful relationship.
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16:10 - 16:13But I think that it's quite interesting
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16:13 - 16:15to know that there is reallymathematical evidence
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16:15 - 16:18to say that you should neverlet the sun go down on your anger.
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16:18 - 16:20So those are my top three tips
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16:20 - 16:23of how maths can help youwith love and relationships.
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16:23 - 16:26But I hopethat aside from their use as tips,
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16:26 - 16:30they also give you a little bit of insightinto the power of mathematics.
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16:30 - 16:34Because for me, equations and symbols aren't just a thing.
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16:34 - 16:39They're a voice that speaks outabout the incredible richness of nature
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16:39 - 16:41and the startling simplicity
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16:41 - 16:45in the patterns that twist and turnand warp and evolve all around us,
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16:45 - 16:48from how the world works to how we behave.
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16:48 - 16:50So I hope that perhaps,for just a couple of you,
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16:50 - 16:53a little bit of insight intothe mathematics of love
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16:53 - 16:56can persuade you to have a little bit more love for mathematics.
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16:56 - 16:58Thank you.
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16:58 - 17:00(Applause)
- Title:
- The Mathematics of Love | Hannah Fry | TEDxBinghamtonUniversity
- Description:
-
Dr. Hannah Fry is a mathematician and complexity scientist from University College London's Centre for Advanced Spatial Analysis. Her work revolves around exploring the patterns in human behavior and applying a mathematical perspective to tackle a wide range of problems across our society. Alongside her academic position, Fry is passionate about sharing the abstract beauty of mathematics with others and demonstrating its importance in our modern world. She has a broad portfolio of media and public engagement activities from schools outreach, math-themed stand-up comedy, YouTube videos and public lectures. Fry also regularly presents the Number Hub strand of BBC Worldwide's YouTube channel, Headsqueeze.
In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDxTalks
- Duration:
- 17:43
Ivana Korom edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity |