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.

• 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.

• 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.

• 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.

• 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.

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.