csci 102: introduction to computational modeling chapter 1: the modeling process

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CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

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Page 1: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

CSCI 102: Introduction to Computational Modeling

Chapter 1: The Modeling Process

Page 2: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

I am never content until I have constructed mechanical model of the subject I am studying. If I succeed in making one, I understand; otherwise I do not.

I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of Science, whatever the matter may be.

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are needed to see this picture.

– William Thomson, Lord Kelvin (1824 - 1907)

Page 3: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

Radio has no future.QuickTime™ and a

decompressorare needed to see this picture.

– William Thomson, Lord Kelvin (1824 - 1907)

Page 4: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

All models are wrong, but some models are useful

– George Box (1919 - )

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Page 5: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

What is Wrong with this Model? What is Useful About It?

Page 6: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

Case Study: Value at Risk

• 1% VaR of $1M: On a given day, there is a 1% chance that the value of your stock portfolio will fall by $1M.

• Let’s build a model….

Page 7: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process
Page 8: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process

Black Swan!

• To me, VaR is charlatanism because it tries to estimate something that is not scientifically possible to estimate, namely the risks of rare events.

- Nassim Taleb

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Page 9: CSCI 102: Introduction to Computational Modeling Chapter 1: The Modeling Process