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The Model Thinker: What You Need to Know to Make Data Work for You
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The Model Thinker: What You Need to Know to Make Data Work for You

3.73  ·  Rating details ·  52 ratings  ·  9 reviews
How anyone can become a data ninja

From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page
Kindle Edition, 398 pages
Published November 27th 2018 by Basic Books
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3.73  · 
Rating details
 ·  52 ratings  ·  9 reviews

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Mel (Epic Reading)
As a professional Business Intelligence Analyst (BIA) this is the perfect non-fiction book for my desk. I do data aggregation, reporting, and analysis at my day job. And we are constantly trying to determine what the best correlation, representation or model is for analysis the data available to us.
Scott E. Page starts us off talking about WHY. This is an often overlooked piece of any business work. The why. Why do we do something? Why do we care? Why use X over Y? And so on...
In this case Pag
I really like the subject of this book. Model thinking is one of the best subjects I have taken in Coursera. The concepts are really useful and practical. It helps you to frame your thinking about numerous things in our world.

I would not give this book a 5 stars because I think this subject is best convey through other format like videos, lectures, or course. The topic is a bit complex especially for those who ate not comfortable with numerical reasoning. By putting it in book format it limited
Professor Page certainly introduces some interesting concepts in The Model Thinker. His overall aim here is to get you to use multiple models in your thinking, and the plethora of models provided will be an aid to any person out there.

That said, I found it rather difficult to get through. My attention wandered far more than I thought it would. I think that is just the nature of non-fiction sometimes. Even when interested in a subject, a book on it is not always enjoyable. Thus, my star rating sh
Alexis Bauer Kolak
The title of this book is a little misleading. While the author provides a clear, informative overview of the different types of models and the kinds of problems they are regularly used to solve, he never touches on examples of where you might want to apply them. I was expecting a little more guidance on what this information means to me.

In spite of that, I could see this being very useful, and it did make me want to read more on some of the topics covered here.
Mar 17, 2019 rated it really liked it  ·  review of another edition
Shelves: rmtd, vuca
Data -> Information -> Knowledge -> Wisdom

Basically sums the "Model Thinking" Course by the same professor.
The style in which the book was written, makes it a perfect handbook/manual for class...
And I guess that regardless of one's background, and with enough openness, you can discern magical phenomena (obviously it's just that we ignore how stuff work), while reading this book.
Now back to the oldest idea about models as mere reductions, and are not reliable or so: Yes they are reductio
Mitch Malone
Jan 05, 2019 rated it really liked it  ·  review of another edition
There are some useful models in here that I've been able to apply directly to my work. The overall thesis—using many models to explain, predict, and act is more helpful than using one—is something that really came into focus.

It's a very dense book with "textbook" style writing. I wish it had more narrative prose to make the reading more enjoyable. There aren't as many real world examples in the book—it's mostly math and visuals of the models themselves.
Feb 18, 2019 rated it really liked it
A good reference for knowing model names. Nothing more. It is not for people without basic statistics, computer science, and math knowledge. And It is not for people who were looking for advanced models. I was not really sure who the author's intended readers are. On the plus side, the book gives a very broad view of the models used in various fields--from economics to epidemiology.
Denis Romanovsky
This is a great source of wisdom. 25 something general prediction models with simple math explanation, good examples and comprehensive insights. Many model approach reasonable as nothing else in this world. Invaluable food for thought!
Bryan Alkire
Good info but the writing is not compelling
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