Fortunately or accidentally, I only have two classes this term. Meanwhile, they separate them into four days, so I only have two-hours class every day from Monday to Thursday. Compared to my previous schedule, it is too relaxing.
An advantage now is that I have enough time to read and think. Today I found Becker's book by chance, when I was browsing the literature on "social economics", or socio-economics. It is quite exciting, and I have realized how deep the water might be- before I was only using my naive intuition that there is something I can contribute soon.
The book I'm talking about now is
Before I was paying more attention solely to network economics, and it turned out to be that they were quite similar to each other in most sense; however, socio-economics is for sure more broad.
Moreover, I took a few hours finishing reading another book,
Salsburg, D. (2002) The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century
From the name, you can see that this book is about basic statistics. To save time, I read its Chinese translation. Not very long, but very exciting - maybe I have been, and will always be attracted by mathematics and statistics. Especially the later one, perhaps due to the fact that I have so many friends in this area, is one field beyond economics that has influenced me the most, and more on the level of conception and methodology than techniques or actual methods.
While reading this book, it reminds me another book I read before, which is about the famous economist Keynes,
Robert Skidelsky, 2005, John Maynard Keynes: 1883-1946: Economist, Philosopher, Statesman
What impressed me most at that time was not Keynes' contribution to economics - although nobody can neglect that, but his ideas on probability. Until now, I still have the wish that one day I want to read Keynes' original book on probability somewhere.
I want to read Becker's book only for the reason that I need an idea for my history paper. One question I have been seeking for the answer for a while: why do we need to care about the network structure? Before, I was only arguing that the "summation is a naive way to draw the group's characteristics"; now it seems that I need to really re-think about this argument. In addition to sum or mean, people have developed distribution to help understand the world; furthermore, from central limit theorem, normal distribution can be utilized in most scenarios. Therefore, under what particular case will summation cause a severe problem?
Another thing I'm thinking about now is after reading the "Lady tasting tea", a term still remains to be explained more clearly: frequency school and Bayesian school's debate on the definition of probability. On one side we are lucky today that following Baye's idea will not be regarded as heterodox any more; on the other side, although his idea itself is very simple, how to make a perfect use of it is still a very tricky and should be dealed with carefully.
I'll stop here for now, and see whether I can gain some new senses soon. This year is too short- I need a longer time to make all things clear.