Model Thinking

五分彩走势图 www.2687b.cn 你将在本课程中学习如何运用模型来思考,并利用它了解我们身边的复杂世界。





32 小时

  • 中文, 英语, 葡萄牙语, 其他
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我们生活在一个繁杂的世界,不同的人、企业和政府相互交织,他们的各种行为结合起来,共同产生新颖、意想不到的各种现象。为此,政治起义、市场崩盘和永无止境的社会趋势浮现在我们眼前,我们如何理解它们呢?运用模型。证据表明,具备模型思维的人表现要优于那些没有这种思维的人。此外,运用大量模型来思考的人,其表现优于只运用一种模型思考的人。 为什么模型会让我们成为更好的思考者? 模型帮助我们更好地组织信息,理清互联网上多如乱麻的数据。模型帮助我们提高准确预测的能力,帮助我们做出更好的决策,采取更有效的策略,甚至可提高我们设计机构和程序的能力。本课中,我将会介绍一组入门模型:首先介绍临界点模型,然后是解释群众智慧的模型,解释有些国家富有而有些国家贫穷的原因的模型,以及帮助企业和政治家作出战略决策的模型。本课涵盖的模型将为后续社会科学课程奠定基础,无论是经济学、政治学、商学或社会学领域。掌握这些材料将为你学习这些进阶课程提供很大帮助。此外,这些模型还能在生活中给予你帮助。 课程的安排方式: 对于每个模型,我会提供简短、易理解的概述讲座。然后,我会深入挖掘每个模型的技术细节。这些技术讲座不要求微积分知识,但会涉及一些代数内容。所有讲座都有对应问题,此外还有一些小测验,甚至期末考试。如果你决定深入研究,并完成所有测验和考试,你将获得结业证明。如果你决定只上入门讲座,以初步了解模型,也是可以的。这门课程是完全免费的,但能助你成为更好的思考者!

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!





Strategic Thinking


完成时间为 3 小时
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.
12 个视频 (总计 124 分钟), 6 个阅读材料, 1 个测验

完成时间为 3 小时
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.
12 个视频 (总计 138 分钟), 1 个阅读材料, 1 个测验

完成时间为 3 小时
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.
12 个视频 (总计 130 分钟), 1 个阅读材料, 1 个测验

完成时间为 3 小时
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.
13 个视频 (总计 132 分钟), 1 个阅读材料, 1 个测验

完成时间为 2 小时
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.
10 个视频 (总计 99 分钟), 1 个阅读材料, 1 个测验

完成时间为 28 分钟
Midterm Exam
1 个测验

完成时间为 2 小时
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.
11 个视频 (总计 116 分钟), 1 个阅读材料, 1 个测验

完成时间为 3 小时
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
10 个视频 (总计 122 分钟), 1 个阅读材料, 1 个测验

完成时间为 2 小时
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.
11 个视频 (总计 79 分钟), 1 个阅读材料, 1 个测验

完成时间为 2 小时
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.
9 个视频 (总计 92 分钟), 1 个阅读材料, 1 个测验

完成时间为 1 小时
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.
8 个视频 (总计 62 分钟), 1 个阅读材料, 1 个测验

完成时间为 1 小时
Final Exam
The description goes here





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