Mathematics 292 - DATA SCIENCE

Computational data analysis is an essential part of modern statistics. This course provides a practical foundation for students to compute with data, by participating in the entire data analysis cycle (from forming a statistical question, data acquisition, cleaning, transforming, modeling and interpretation). This course will introduce students to tools for data management, storage and manipulation that are common in data science and will apply those tools to real scenarios. Students will undertake practical analyses using real, large, messy data sets using modern computing tools (e.g. R, SQL) and learn to think statistically in approaching all of these aspects of data analysis. Prerequisites: CSC 111 or MTH 205/CSC 205 plus an introductory statistics course (e.g. MTH 245, ECO 220 or AP Statistics), CSC 107 recommended, but not required. Some programming experience is required.