EC 232 - Exploratory Data Analysis

4 credits
Explores data and applications to real-world problems. Covers time-series and cross-sectional data, analysis of skewness and outliers, methods of averaging for variables as flows or stocks, and applies nae forecasting techniques to real-world settings. Approved for University Studies (Quantitative Reasoning-Strand D). Prerequisite(s): MTH 95, Level II
Grade mode designated on a CRN basis each term. Students should consult current term schedule.