About this Course
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!
Globe

100% online course

Start instantly and learn at your own schedule.
Clock

Approx. 32 hours to complete

Suggested: 4-8 hours/week
Comment Dots

English

Subtitles: English, Portuguese (Brazilian), Turkish, Ukrainian, Chinese (Simplified)

Skills you will gain

EconomicsDecision-MakingDecision AnalysisManagement
Globe

100% online course

Start instantly and learn at your own schedule.
Clock

Approx. 32 hours to complete

Suggested: 4-8 hours/week
Comment Dots

English

Subtitles: English, Portuguese (Brazilian), Turkish, Ukrainian, Chinese (Simplified)

Syllabus - What you will learn from this course

1

Section
Clock
3 hours to complete

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. ...
Reading
12 videos (Total 124 min), 6 readings, 1 quiz
Video12 videos
Why Model?8m
Intelligent Citizens of the World11m
Thinking More Clearly10m
Using and Understanding Data10m
Using Models to Decide, Strategize, and Design15m
Sorting and Peer Effects Introduction5m
Schelling's Segregation Model11m
Measuring Segregation11m
Peer Effects6m
The Standing Ovation Model18m
The Identification Problem10m
Reading6 readings
Welcome10m
Grading Policy10m
Course FAQ10m
Syllabus10m
Help us learn more about you!10m
Segregation and Peer Effects10m
Quiz1 practice exercises
Why Model? & Segregation and Peer Effects12m

2

Section
Clock
3 hours to complete

Aggregation & Decision Models

In this section, we explore the mysteries of aggregation, i.e. adding things up. We start by considering how numbers aggregate, focusing on the Central Limit Theorem. We then turn to adding up rules. We consider the Game of Life and one dimensional cellular automata models. Both models show how simple rules can combine to produce interesting phenomena. Last, we consider aggregating preferences. Here we see how individual preferences can be rational, but the aggregates need not be.There exist many great places on the web to read more about the Central Limit Theorem, the Binomial Distribution, Six Sigma, The Game of LIfe, and so on. I've included some links to get you started. The readings for cellular automata and for diverse preferences are short excerpts from my books Complex Adaptive Social Systems and The Difference Respectively....
Reading
12 videos (Total 138 min), 1 reading, 1 quiz
Video12 videos
Central Limit Theorem18m
Six Sigma5m
Game of Life14m
Cellular Automata18m
Preference Aggregation12m
Introduction to Decision Making5m
Multi-Criterion Decision Making8m
Spatial Choice Models11m
Probability: The Basics10m
Decision Trees14m
Value of Information8m
Reading1 readings
Decision Models10m
Quiz1 practice exercises
Aggregation & Decision Models16m

3

Section
Clock
3 hours to complete

Thinking Electrons: Modeling People & Categorical and Linear Models

In this section, we study various ways that social scientists model people. We study and contrast three different models. The rational actor approach, behavioral models, and rule based models . These lectures provide context for many of the models that follow. There's no specific reading for these lectures though I mention several books on behavioral economics that you may want to consider. Also, if you find the race to the bottom game interesting just type "Rosemary Nagel Race to the Bottom" into a search engine and you'll get several good links. You can also find good introductions to "Zero Intelligence Traders" by typing that in as well....
Reading
12 videos (Total 130 min), 1 reading, 1 quiz
Video12 videos
Rational Actor Models16m
Behavioral Models12m
Rule Based Models12m
When Does Behavior Matter?12m
Introduction to Linear Models4m
Categorical Models15m
Linear Models8m
Fitting Lines to Data11m
Reading Regression Output11m
From Linear to Nonlinear6m
The Big Coefficient vs The New Reality11m
Reading1 readings
Categorical and Linear Models10m
Quiz1 practice exercises
Modules Thinking Electrons: Modeling People & Categorical and Linear Models20m

4

Section
Clock
3 hours to complete

Tipping Points & Economic Growth

In this section, we cover tipping points. We focus on two models. A percolation model from physics that we apply to banks and a model of the spread of diseases. The disease model is more complicated so I break that into two parts. The first part focuses on the diffusion. The second part adds recovery. The readings for this section consist of two excerpts from the book I'm writing on models. One covers diffusion. The other covers tips. There is also a technical paper on tipping points that I've included in a link. I wrote it with PJ Lamberson and it will be published in the Quarterly Journal of Political Science. I've included this to provide you a glimpse of what technical social science papers look like. You don't need to read it in full, but I strongly recommend the introduction. It also contains a wonderful reference list....
Reading
13 videos (Total 132 min), 1 reading, 1 quiz
Video13 videos
Percolation Models11m
Contagion Models 1: Diffusion7m
Contagion Models 2: SIS Model9m
Classifying Tipping Points8m
Measuring Tips13m
Introduction To Growth6m
Exponential Growth10m
Basic Growth Model13m
Solow Growth Model11m
Will China Continue to Grow?11m
Why Do Some Countries Not Grow?11m
Piketty's Capital: The Power of Simple Model8m
Reading1 readings
Economic Growth10m
Quiz1 practice exercises
Modules Tipping Points & Economic Growth18m

5

Section
Clock
2 hours to complete

Diversity and Innovation & Markov Processes

In this section, we cover some models of problem solving to show the role that diversity plays in innovation. We see how diverse perspectives (problem representations) and heuristics enable groups of problem solvers to outperform individuals. We also introduce some new concepts like "rugged landscapes" and "local optima". In the last lecture, we'll see the awesome power of recombination and how it contributes to growth. The readings for this chapters consist on an excerpt from my book The Difference courtesy of Princeton University Press....
Reading
10 videos (Total 99 min), 1 reading, 1 quiz
Video10 videos
Perspectives and Innovation16m
Heuristics9m
Teams and Problem Solving11m
Recombination11m
Markov Models4m
A Simple Markov Model11m
Markov Model of Democratization8m
Markov Convergence Theorem10m
Exapting the Markov Model10m
Reading1 readings
Markov Processes10m
Quiz1 practice exercises
Diversity and Innovation & Markov Processes12m

6

Section
Clock
28 minutes to complete

Midterm Exam

...
Reading
1 quiz
Quiz1 practice exercises
Modules 1-1028m

7

Section
Clock
2 hours to complete

Lyapunov Functions & Coordination and Culture

Models can help us to determine the nature of outcomes produced by a system: will the system produce an equilibrium, a cycle, randomness, or complexity? In this set of lectures, we cover Lyapunov Functions. These are a technique that will enable us to identify many systems that go to equilibrium. In addition, they enable us to put bounds on how quickly the equilibrium will be attained. In this set of lectures, we learn the formal definition of Lyapunov Functions and see how to apply them in a variety of settings. We also see where they don't apply and even study a problem where no one knows whether or not the system goes to equilibrium or not....
Reading
11 videos (Total 116 min), 1 reading, 1 quiz
Video11 videos
The Organization of Cities12m
Exchange Economies and Externalities9m
Time to Convergence and Optimality8m
Lyapunov: Fun and Deep8m
Lyapunov or Markov7m
Coordination and Culture3m
What Is Culture And Why Do We Care?15m
Pure Coordination Game13m
Emergence of Culture11m
Coordination and Consistency 17m
Reading1 readings
Coordination and Culture10m
Quiz1 practice exercises
Lyapunov Functions & Coordination and Culture20m

8

Section
Clock
3 hours to complete

Path Dependence & Networks

In this set of lectures, we cover path dependence. We do so using some very simple urn models. The most famous of which is the Polya Process. These models are very simple but they enable us to unpack the logic of what makes a process path dependent. We also relate path dependence to increasing returns and to tipping points. The reading for this lecture is a paper that I wrote that is published in the Quarterly Journal of Political Science...
Reading
10 videos (Total 122 min), 1 reading, 1 quiz
Video10 videos
Urn Models16m
Mathematics on Urn Models14m
Path Dependence and Chaos11m
Path Dependence and Increasing Returns12m
Path Dependent or Tipping Point9m
Networks7m
The Structure of Networks19m
The Logic of Network Formation10m
Network Function13m
Reading1 readings
Networks10m
Quiz1 practice exercises
Path Dependence & Networks20m

9

Section
Clock
2 hours to complete

Randomness and Random Walks & Colonel Blotto

In this section, we first discuss randomness and its various sources. We then discuss how performance can depend on skill and luck, where luck is modeled as randomness. We then learn a basic random walk model, which we apply to the Efficient Market Hypothesis, the ideas that market prices contain all relevant information so that what's left is randomness. We conclude by discussing finite memory random walk model that can be used to model competition. The reading for this section is a paper on distinguishing skill from luck by Michael Mauboussin....
Reading
11 videos (Total 79 min), 1 reading, 1 quiz
Video11 videos
Sources of Randomness5m
Skill and Luck8m
Random Walks12m
Random Walks and Wall Street7m
Finite Memory Random Walks8m
Colonel Blotto Game1m
Blotto: No Best Strategy7m
Applications of Colonel Blotto7m
Blotto: Troop Advantages6m
Blotto and Competition10m
Reading1 readings
Colonel Blotto10m
Quiz1 practice exercises
Randomness and Random Walks & Colonel Blotto16m

10

Section
Clock
2 hours to complete

Prisoners' Dilemma and Collective Action & Mechanism Design

In this section, we cover the Prisoners' Dilemma, Collective Action Problems and Common Pool Resource Problems. We begin by discussion the Prisoners' Dilemma and showing how individual incentives can produce undesirable social outcomes. We then cover seven ways to produce cooperation. Five of these will be covered in the paper by Nowak and Sigmund listed below. We conclude by talking about collective action and common pool resource problems and how they require deep careful thinking to solve. There's a wonderful piece to read on this by the Nobel Prize winner Elinor Ostrom....
Reading
9 videos (Total 92 min), 1 reading, 1 quiz
Video9 videos
The Prisoners' Dilemma Game13m
Seven Ways To Cooperation15m
Collective Action and Common Pool Resource Problems7m
No Panacea6m
Mechanism Design4m
Hidden Action and Hidden Information9m
Auctions19m
Public Projects12m
Reading1 readings
Mechanism Design10m
Quiz1 practice exercises
Prisoners' Dilemma and Collective Action & Mechanism Design18m

11

Section
Clock
1 hour to complete

Learning Models: Replicator Dynamics & Prediction and the Many Model Thinker

In this section, we cover replicator dynamics and Fisher's fundamental theorem. Replicator dynamics have been used to explain learning as well as evolution. Fisher's theorem demonstrates how the rate of adaptation increases with the amount of variation. We conclude by describing how to make sense of both Fisher's theorem and our results on six sigma and variation reduction. The readings for this section are very short. The second reading on Fisher's theorem is rather technical. Both are excerpts from Diversity and Complexity....
Reading
8 videos (Total 62 min), 1 reading, 1 quiz
Video8 videos
The Replicator Equation13m
Fisher's Theorem11m
Variation or Six Sigma5m
Prediction2m
Linear Models5m
Diversity Prediction Theorem11m
The Many Model Thinker7m
Reading1 readings
Prediction and The Many Model Thinker10m
Quiz1 practice exercises
Learning Models: Replicator Dynamics & Prediction and the Many Model Thinker12m

12

Section
Clock
1 hour to complete

Final Exam

The description goes here...
Reading
1 reading, 1 quiz
Reading1 readings
Post-course Survey10m
Quiz1 practice exercises
Modules 12-2126m
4.8
Direction Signs

10%

started a new career after completing these courses
Briefcase

83%

got a tangible career benefit from this course

Top Reviews

By YKApr 7th 2018

The course presents a multitude of models that enable us to analyze human and systems behavior and interactions. By making implicit assumptions explicit we can understand real world processes better.

By GKFeb 25th 2017

Great content and lectures, that possibly provides new dimensions to look/explain the situation in context, I guess I will comeback for references to continue with this journey in to 'Model Thinking'

Instructor

Avatar

Scott E. Page

Professor of Complex Systems, Political Science, and Economics

About University of Michigan

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

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