Model Thinking

Start Date: 02/23/2020

Course Type: Common Course

Course Link:

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About 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!

Course Syllabus

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.

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Course Introduction

Model Thinking and Data Exploration In part two of this course, we will dive into the modeling and visualization techniques used in many natural and social systems, including population genetics, population dynamics, urbanization, energy markets, transportation and the environment. We will cover models for forecasting, diversification, diversification of returns, and diversification of investment opportunities. We will also cover the basic concepts of model-thinking and exploratory data analysis. We will use Python to implement key elements of model-thinking, including modeling variables and introducing the tools of exploratory data analysis. Our goal is to get you up and running with modeling, data visualization and exploratory analysis skills in no time! Upon completing this course, you will be able to: * Model and visualize natural and social systems * Describe the major components of many natural and social systems * Apply the major tools of model-thinking and exploratory data analysis * Develop and implement simple models for internal and external analysis * Explain the basic concepts and terminology of model-thinking and exploratory data analysis * Explain the difference between exploratory data analysis and modeling * Apply the tools of exploratory data analysis and modeling An important note: The course assumes prior knowledge of Python and linear algebra. If you are unsure, please check in the Resources area or on our website at: to Model Thinking and Data Exploration Exploratory Data

Course Tag

Modeling Economics Decision-Making Strategic Thinking

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Article Example
Scott E. Page In addition to teaching at Michigan, Page also instructs the Teaching Company educational video series "Understanding Complexity" and the online "Model Thinking" course created by Coursera.
Scott E. Page In early 2013, Page gave an online-course on the MOOC-platform Coursera called "Model Thinking". Due to massive participation this course is repeated and will be repeated several times.
Critical thinking Critical thinking is an important element of all professional fields and academic disciplines (by referencing their respective sets of permissible questions, evidence sources, criteria, etc.). Within the framework of scientific skepticism, the process of critical thinking involves the careful acquisition and interpretation of information and use of it to reach a well-justified conclusion. The concepts and principles of critical thinking can be applied to any context or case but only by reflecting upon the nature of that application. Critical thinking forms, therefore, a system of related, and overlapping, modes of thought such as anthropological thinking, sociological thinking, historical thinking, political thinking, psychological thinking, philosophical thinking, mathematical thinking, chemical thinking, biological thinking, ecological thinking, legal thinking, ethical thinking, musical thinking, thinking like a painter, sculptor, engineer, business person, etc. In other words, though critical thinking principles are universal, their application to disciplines requires a process of reflective contextualization.
Vertical thinking This instrument, otherwise known as the SO-LAT, evaluates analytic versus holistic thinking styles. The analytic thinking mode can be compared to vertical thinking, whereas holistic thinking can be compared to lateral thinking.
Visual thinking Visual thinking, also called visual/spatial learning or picture thinking is the phenomenon of thinking through visual processing.
Lange model The model is sometimes called the "Lange–Lerner" model. Abba Lerner wrote a series of articles that greatly influenced Lange's thinking. For example, Lerner (1938) caused Lange to re-write his 1936 and 1937 articles on market socialism, before they were re-published as chapters in a 1938 book. Lerner (1938) influenced Lange's thinking on social dividend payments. Lerner (1944) also argued that investment in the Lange model would inevitably be politicized.
Thinking machine Thinking machine or thinking machines may refer to:
Convergent thinking No personality effects on convergent thinking were found, suggesting that the Big Five personality traits are a better predictor of divergent thinking than convergent thinking or that all types of individuals engage in convergent thinking regardless of their personality.
Walter Model Having restored Ninth Army's front, Model set about holding it. His defensive doctrine, which combined conventional thinking with his own tactical innovations, was based on the following principles:
Mental model In the simplification of reality, creating a model can find a sense of reality, seeking to overcome systemic thinking and system dynamics.
Strategic thinking In the view of F. Graetz, strategic thinking and planning are “distinct, but interrelated and complementary thought processes” that must sustain and support one another for effective strategic management. Graetz's model holds that the role of strategic thinking is "to seek innovation and imagine new and very different futures that may lead the company to redefine its core strategies and even its industry". Strategic planning's role is "to realise and to support strategies developed through the strategic thinking process and to integrate these back into the business".
Critical thinking "First wave" logical thinking consisted of understanding the connections between two concepts or points in thought. It followed a philosophy where the thinker was removed from the train of thought and the connections and the analysis of the connect was devoid of any bias of the thinker. Kerry Walter’s describes this ideology in her essay Beyond Logicism in Critical Thinking, "A logistic approach to critical thinking conveys the message to students that thinking is legitimate only when it conforms to the procedures of informal (and, to a lesser extent, formal) logic and that the good thinker necessarily aims for styles of examination and appraisal that are analytical, abstract, universal, and objective. This model of thinking has become so entrenched in conventional academic wisdom that many educators accept it as canon" (Walters, 1994, p. 1). The adoption of these principals parallel themselves with the increasing reliance on quantitative understanding of the world.
Causal thinking Causal thinking follows the line given by a sequence of cause-effects relations and therefore causal thinking is described by Binder as thinking in points. Similarly, von Collani compares the prevailing causal thinking in science with logical thinking since it is based on a sequence, the logical relations "if a then b".
Divergent thinking The psychologist J.P. Guilford first coined the terms convergent thinking and divergent thinking in 1956.
Design thinking Taking Design Thinking to Schools identifies the following design thinking process:
Critical thinking In the ‘second wave’ of critical thinking, as defined by Kerry S. Walters (Re-thinking Reason, 1994, p. 1 ), many authors moved away from the logocentric mode of critical thinking that the ‘first wave’ privileged, especially in institutions of higher learning. Walters summarizes logicism as "the unwarranted assumption that good thinking is reducible to logical thinking" (1994, p. 1).
Design thinking Design thinking employs divergent thinking as a way to ensure that many possible solutions are explored in the first instance, and then convergent thinking as a way to narrow these down to a final solution. Divergent thinking is the ability to offer different, unique or variant ideas adherent to one theme while convergent thinking is the ability to find the "correct" solution to the given problem. Design thinking encourages divergent thinking to ideate many solutions (possible or impossible) and then uses convergent thinking to prefer and realize the best resolution.
Thinking Maps In 1970, Innovative Sciences, Inc. (ISI) was founded by Charles Adams in order to "improve the thinking and problem-solving abilities of the work force" (Thinking Maps, Inc., 2011). Over the next eighteen years, ISI created a variety of developmentally appropriate materials, or "content-based thinking skills," for schools based on research from student reading performance and different educational teaching models (Thinking Maps, Inc., 2011). In 1988, David Hyerle wrote Expand Your Thinking, which was the first resource where his Thinking Maps were published, and at that point, he began training educators to use his Thinking Maps (Thinking Maps, Inc., 2011). In 1994, test results indicated that "Thinking Maps significantly affect[ed] standardized and qualitative measures of student performance" (Thinking Maps Inc., 2011). After more success and schools nationwide piloting Thinking Maps, ISI changed its name to Thinking Maps, Inc. in 2004 to "better promote its mission" (Thinking Maps, Inc., 2011). Today, thousands of teachers across America have been trained in using and implementing Thinking Maps in their classrooms. Thinking Maps are also being promoted in the United Kingdom, Canada, New Zealand, and Australia (Thinking Maps, Inc., 2011).
Design thinking The process is characterized by the alternation of divergent and convergent thinking, typical of design thinking process.
Visual thinking "Real picture thinkers", those persons who use visual thinking almost to the exclusion of other kinds of thinking, make up a smaller percentage of the population. Research by child development theorist Linda Kreger Silverman suggests that less than 30% of the population strongly uses visual/spatial thinking, another 45% uses both visual/spatial thinking and thinking in the form of words, and 25% thinks exclusively in words. According to Kreger Silverman, of the 30% of the general population who use visual/spatial thinking, only a small percentage would use this style over and above all other forms of thinking, and can be said to be true "picture thinkers".