Week 2- how can I improve? The direction and goal
As the term goes on, I have a deeper understanding of my learning direction and read more literature.
After reading the literature, I found the universal inequality in the world regarding inequality and exclusion. In the literature, literalized sociological problems are often solved with mathematical formulas, and corresponding conclusions are finally drawn. The analysis is reasonable and convincing, which is what I need to learn. My undergraduate major is Accounting, so I am very interested in some numbers and formulas. Although I don’t understand most of them very well, I still love them. I hope I can understand more one day.
For future projects, I would like to focus on relevant content, such as whether the ratio of males to females, social status and education level are directly related to the health level of a country? Do these inequalities differ across countries and how much difference?
Although I temporarily for some understanding of the concept of or at the level of fur, I need to learn more, have a more comprehensive cognition of it, and I am interested in the combination of inequality study and how it will go with accounting, statistics, mathematics, python, to make a better understanding to the research of inequality. For example, to analyze whether a certain population in a certain stage is normally distributed, or conforms to what function curve? Is it relevant to the macroeconomic policy of the country and the world? Is it positive or negative? I don’t know if I can do it, but I know I need more knowledge and understanding to do it.
It is worth mentioning that I like the course Text Remix very much. Through it, I will learn Python to mine some data and articles I want or need, and at the same time exercise my understanding and thinking of data.
Last but not least, I hope we can learn more next week, and I hope everyone had a good time.
Ye Wu, it’s great to hear that you have started getting a sense of the direction you’d like to explore on the programme. I was just wondering, following the intensives we had on Monday and Tuesday, how has your view on data types (quantitative data vs qualitative data) and their applications changed, if at all?