Welcome to Yili Wang’s digital portfolio!
My name is Yili Wang, a fourth-year Applied Statistics student at UC Davis with expected graduation in December 2017. I am from Beijing and my hobbies are playing tennis and stock investment (even though I lose a lot.. but I am still optimistic about the market!) I am passionate about programming in python and want to seek for a career in the industry of Data Science and Quantitative Finance.
Here are some projects I did. I hope these will make you feel how amazing the programming world is! Enjoy!
World GDP Growth and Population Growth Analysis
Click here for details of the project
Abstract: In the data of the World Development Indicators from the World Bank, it contains over a thousand annual indicators of economic development from hundreds of countries around the world. In the project, we explore the world GDP growth, the population, and other indicators from selected years which reflecting four phrase of world development: 1974, 1994, 2008, 2014. The purposes of the project are to observe the changes of GDP and population from countries over the world and to predict the these variables from a selected country, which is the United States.
Race, School Ratings, and Real Estate: What affects home price in California?
Click here for details of the project
Abstract: When it comes to home buying market, people usually need to consider many characteristics of the house, such as number of bedrooms and bathrooms, lot size, garage, backyard, etc. However, there are actually much more factors need to be thought about beyond the house itself. For example, public school ratings and crime situation. Accroding to a national study conducted in 2013, public school ratings in the district can affect the homes’ values, which leads to an average premium of $50 a square foot. Besides, racial composition of the neighborhood also influence home buyers’ decisions. For most of the time, school ratings and racial composition interact with each other and mutually pose impact on real estate price. This project focuses on researching the relationship between public school rating and racial composition and their influences in home prices. We examine the crime occurrence and house price. By the end, web scraping is used to predict the trend of the house price.