Fall 2019

Data Science

Listed in: Mathematics and Statistics, as STAT-231

Moodle site: Section 02

Faculty

Katharine F. Correia (Section 01)
Nicholas J. Horton (Section 02)

Description

Computational data analysis is an essential part of modern statistics and data science. This course provides a practical foundation for students to think with data by participating in the entire data analysis cycle. Students will generate statistical questions and then address them through data acquisition, cleaning, transforming, modeling, and interpretation. This course will introduce students to tools for data management and wrangling that are common in data science and will apply those tools to real-world applications. Students will undertake practical analyses of large, complex, and messy data sets leveraging modern computing tools.

Requisite: STAT 111 or STAT 135 and COSC 111 or consent of the instructor. Limited to 24 students. Fall semester: Professors Correia and Professor Horton. Spring semester: Professor Correia. 

If Overenrolled: priority for sophomores then STAT majors

Cost: 0 ?

Keywords

Quantitative Reasoning, Science & Math for Non-majors

Offerings

2019-20: Offered in Fall 2019 and Spring 2020
Other years: Offered in Fall 2017, Spring 2018, Fall 2018