— Applied Data Analysis

Prerequisites & course information

Course Description: Data exploration and integrity; data collection and cleaning techniques; examination of data types, handling missing data and outliers. Coverage of analytical regression techniques encompasses parametric (OLS), semi-parametric (logistic), and non-parametric (GLM, kernel regressions) models. Application of techniques on diverse real-world datasets using various software tools. Learning Activities: Lecture 4 hour(s). Cross Listing: ECI 254 . Grade Mode: Letter. Learning Activities: Lecture 4 hour(s). Cross Listing: ECI 254 . Grade Mode: Letter.