MSAN 593 - Exploratory Data Analysis

Credits: 1

Before we can begin to apply rigorous statistical tools to data, we often need to approach our data intuitively, and look for meaningful associations and surprising patterns, detect outliers and anomalies, formulate hypotheses. This practice is commonly referred to as Exploratory Data Analysis (EDA). Successful exploratory data analysis depends on the ability to manipulate and visualize data. This class introduces various concepts in EDA with an emphasis on data manipulation in R.

Restriction: Restricted to Graduate level SC