This project is the final project for the course AAS in spring 2019. It mainly focuses on datasets collected by some people from Law Shool in RUC. Different from model-based applications of some theoretical methodologies, I concentrate more attention on tasks like high-efficient data preprocessing, user-friendly EDA, giving reasonable explaination or telling the stories based on necessary statistical tools. Here are the reasons why I choose to do so.
- Firstly, these datasets are not industrial-level-datas, which are good enough to feed model directly. The content in the datasets are mixutre of text and numbers, and some feature are kind of wierd. Worsely, many missing values exist.
- Secondly, this datasets are coming from real life. On many occasions, people want us to give them good explaination of the results analyzed by advanced, complicated models.
Because of divided data tables and seperate tasks, as well as for increasing readability, I save some core parts in different branches of this project. This file is a brief introduction for this AAS project. In different branches, there are codes file and several brief comments for using what I learned in AAS to solve problems in reality.
- Codes are in 'code' directory.
- Data are in 'data' directory.
- Final reprot is the 'document.pdf' file in 'final report'.
Have a good day!
All data preparation and analyses are reproduced, as well as all Figures in the report.
All codes are in the 'code' directory, run them as their order in the names.
I combine them into file 'Reproduce.R'.