Part Five: DATA
Chapter 22. The New Normal
Bell curves are out. Fat tails are in.
This part is about probabilities. Chapter 22 starts with dispersion graphs and explains the nature of the normal or bell curve and the L-curves. The interesting thing about the bell curve is that even though you can’t know the individual behavior of a particular subject that’s part of the population you’re studying, you can predict the behavior of the whole group. You can see this in many areas in your life, that there’s no way to predict the behavior of an individual, but you can have a pretty accurate prediction of how a group would behave. The other part of the chapter talks about the L-curves. These curves are a better explanation of some phenomena of distribution.
Chapter 23. Chances Are
The improbable thrills of probability theory.
This chapter introduces probability theory. Basically, it’s about the probability that some event A happens, given (or conditional upon) the occurrence of some other event B. He gives some examples, from finding the probability of breast cancer in certain population to the probability that O. J. Simpson murdered his wife. Finally, there are many things and ways we can use to state the probability of some event, but we must remember that many other factors are happening at the same time, so our probability might be very far from reality. One book that he mentions that caught my attention is Calculated Risks by Gerd Gigerenzer.
Chapter 24. Untangling the Web
How Google solved the Zen riddle of Internet search using linear algebra.
Probability has helped us in many ways, and Google by solving the ranking of the web pages is one of them. This chapter explains how Google was capable of computing an algorithm that could calculate the links one page received from others and give to others. This way, the pages would get a ranking from 0 to 1, and 1 would be the total sum of the rankings. By doing this, you are able to classify the pages by ranking and make your search engine be more efficient with the passing of time.
Bell curves are out. Fat tails are in.
This part is about probabilities. Chapter 22 starts with dispersion graphs and explains the nature of the normal or bell curve and the L-curves. The interesting thing about the bell curve is that even though you can’t know the individual behavior of a particular subject that’s part of the population you’re studying, you can predict the behavior of the whole group. You can see this in many areas in your life, that there’s no way to predict the behavior of an individual, but you can have a pretty accurate prediction of how a group would behave. The other part of the chapter talks about the L-curves. These curves are a better explanation of some phenomena of distribution.
Chapter 23. Chances Are
The improbable thrills of probability theory.
This chapter introduces probability theory. Basically, it’s about the probability that some event A happens, given (or conditional upon) the occurrence of some other event B. He gives some examples, from finding the probability of breast cancer in certain population to the probability that O. J. Simpson murdered his wife. Finally, there are many things and ways we can use to state the probability of some event, but we must remember that many other factors are happening at the same time, so our probability might be very far from reality. One book that he mentions that caught my attention is Calculated Risks by Gerd Gigerenzer.
Chapter 24. Untangling the Web
How Google solved the Zen riddle of Internet search using linear algebra.
Probability has helped us in many ways, and Google by solving the ranking of the web pages is one of them. This chapter explains how Google was capable of computing an algorithm that could calculate the links one page received from others and give to others. This way, the pages would get a ranking from 0 to 1, and 1 would be the total sum of the rankings. By doing this, you are able to classify the pages by ranking and make your search engine be more efficient with the passing of time.