IE 5200: Engineering Problem Solving with R
Credits: 3. Contact Hours: Lecture 3.
Introduction to data analytics using R programming language. Data manipulation. Exploratory data analysis via basic graphics. Basic statistical analysis including statistical tests and linear regression. R Markdown. Simulation by replicating a calculation. Conditional expressions, loops, and functions. High level data visualizations using ggplot graphics. Data extraction from text. Optimization via R build-in functions. Logistic regression. High performance computing tools. Project required for graduate credits. (Typically Offered: Spring)