This is my project submissions for Udacity Data Analyst Nanodegree program completed in January 2016.
- Analyzed the Stroop effect using descriptive statistics to prove an intuition about the data.
- Included a very detailed explanation on the statistical tests used in the analysis.
Project 2: [Analysing The NYC Subway Dataset](./New York Subway/Analyzing the NYC Subway Dataset.md)
- Used a couple of statistical tools to study whether the ridership of New York Subway increases in rainy days.
- Issues of multicollinearity were also investigated and analyzed.
Project 3: Wrangle OpenStreetMaps Data
- Wrangled and OpenStreetMaps data in Greater London area with MongoDB.
- Validated the postcodes in this dataset.
- Analysed a few features in this dataset, including user contributions, amenities and transportation network.
Project 4: Explore and Summarize Data
- Explored a courses statistics dataset released by edX, one of the biggest MOOC platform.
- Investigated the correlations between the registrants' information and their performances in the courses.
- More than 20 figures was included in the project file to visulize those features in the dataset.
Project 5: Identifying Fraud from Enron Email
- Identify person of interest (poi) in Enron scandal from a given dataset with a number of machine learning algorithms and data preprocessing methods.
- Both recall and precision of the presented model can achieve more than 0.3.
Project 6: Make Effective Data Visualization
The project visualizes the evolution of three-pointers in the NBA. This visualization allows readers to explore and compare several three-pointer statistics of each NBA team since 1990.