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From the course by University of Michigan

Model Thinking

1109 ratings

University of Michigan

Model Thinking

1109 ratings

We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians. The models covered in this class provide a foundation for future social science classes, whether they be in economics, political science, business, or sociology. Mastering this material will give you a huge leg up in advanced courses. They also help you in life. Here's how the course will work. For each model, I present a short, easily digestible overview lecture. Then, I'll dig deeper. I'll go into the technical details of the model. Those technical lectures won't require calculus but be prepared for some algebra. For all the lectures, I'll offer some questions and we'll have quizzes and even a final exam. If you decide to do the deep dive, and take all the quizzes and the exam, you'll receive a Course Certificate. If you just decide to follow along for the introductory lectures to gain some exposure that's fine too. It's all free. And it's all here to help make you a better thinker!

From the lesson

Why Model & Segregation/Peer Effects

In these lectures, I describe some of the reasons why a person would want to take a modeling course. These reasons fall into four broad categories: 1)To be an intelligent citizen of the world 2) To be a clearer thinker 3) To understand and use data 4) To better decide, strategize, and design. There are two readings for this section. These should be read either after the first video or at the completion of all of the videos.We now jump directly into some models. We contrast two types of models that explain a single phenomenon, namely that people tend to live and interact with people who look, think, and act like themselves. After an introductory lecture, we cover famous models by Schelling and Granovetter that cover these phenomena. We follows those with a fun model about standing ovations that I wrote with my friend John Miller.

Thanks and Welcome3:58

Intelligent Citizens of the World11:30

Thinking More Clearly10:50

Using and Understanding Data10:14

Using Models to Decide, Strategize, and Design15:25

Meet the Instructors

Scott E. Page
Professor of Complex Systems, Political Science, and Economics
Center for the Study of Complex Systems

Hi, my name is Scott Page, I'm a professor of complex system,

political science and economics at the University of Michigan.

And I'd like to welcome you to a new version of Model Thinking.

Model Thinking was the first MOOC offered by the University of Michigan, in 2012.

Since that time, more than a half a million people have taken the course.

So, I thought I'd take this opportunity to share with you some of the feedback I've

gotten from the students, and some of the things that I think have been, sort of,

most interesting about the course and most useful.

So first, one thing that the students have found is just how practical the course is.

So, what the course is going to do is teach you a whole bunch of models.

And those models actually get played out in the real world.

So, let me give you some examples.

So in the summer of 2014, Ebola was spreading in Africa.

And there was a question of how do you model that?

Well, the Center for Disease Control released to the public an SIR type model.

It was actually an SIIR model,

where it was a susceptible infected incubated and recovery.

Well, this is one of the models that we cover in class.

It's one thing that was great is that I got a lot of emails from students,

and there's a lot of discussion among people who've taken the course

about how it's so interesting.

Because they took the model thinking class, they could actually go in and

work with this model that was issued by the Center for Disease Control.

So real policy in the real world

is being done using the same sorts of models you'll use in this class.

Now it's also the case that there's models that we use in this class that are used in

ways that you've never even imagined.

So we play with the mark off models,

so mark up models where we look at things like transitions to the democracy, and

transitions out of poverty, and even whether your relationship is happy.

And what you can find now in the web if you look up you'll see things like mark up

models and video segmentation.

So one theme in the course that we'll about is a lot is how,

when you learn a model, you can apply is in lots of really unexpected places.

In video segmentation of markup models was one that I personally never anticipated.

Another theme is the course is going to be mini models to one.

Now once you've got a whole set of models you can apply them in lots of places.

When 2014 when the World Cup was going on,

people from all over the world were watching soccer.

But it's also the case that people from all the world are taking the models

thinking course.

And though it was fun you're seeing all the different ways people were applying

models from the course.

The kernel model, zero some gain models, right?

The success versus luck model that we covered in the linear equations

segment of the course, and applying those to the World Cup,

because it's fascinating seeing this many to one approach

play out in again something that I didn't really anticipate, the World Cup.

And then finally, I think one thing that's been most interesting about how the course

has played out is how particular things in the course have really resonated.

So one of the ideas that we'll talk about in the course is crowdsourcing.

So how is it that you can sort of tap into the wisdom of crowds to solve problems,

make predictions that sort of stuff.

Well since 2012 when the course first was introduced, crowdsourcing has taken off.

And what you'll see if you look into the literature of crowdsourcing or

even looking in investment companies that use crowdsourcing,

is you'll see how important models have been in developing these new platforms.

And then last,

I just want to say a big thank you to everyone who's taken the course and

also, those of you who take the course this time, just really get engaged.

because one of the things I think that's most rewarding for me.

You have tremendous amount of effort that people put into the course.

Including, doing things like writing graphical representations of everything

they've learned.

Writing long papers on sort of what they've done.

The Australian military even wrote a 50 page summery of the course that they hand

out to new recruits.

So, it's just been a personally very rewarding thing for me to see how much

energy, effort, care, concern that people of couldn't to there own studies.

And how much they've learned by taking this course.

So, I hope you have fabulous time and looking for

interacting with you online and then enjoy model thinking.

Thank you very much.

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