Listed in: Mathematics and Statistics, as STAT-231
Katharine F. Correia (Sections 01 and 02)
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 and Spring semesters. Professor Correia.
If Overenrolled: priority for sophomores then STAT majors
Cost: $100 ?
Section 01
Tu 10:10 AM - 11:30 AM ONLI ONLI
Th 10:10 AM - 11:30 AM ONLI ONLI
Section 02
Tu 01:30 PM - 02:50 PM ONLI ONLI
Th 01:30 PM - 02:50 PM ONLI ONLI
This is preliminary information about books for this course. Please contact your instructor or the Academic Coordinator for the department, before attempting to purchase these books.
Section(s) | ISBN | Title | Publisher | Author(s) | Comment | Book Store | Price |
---|---|---|---|---|---|---|---|
All | Modern Data Science with R | Boca Raton, FL: CRC Press, 2017 | Baumer, Benjamin S., Daniel T. Kaplan, and Nicholas J. Horton | Amherst Books | TBD |
These books are available locally at Amherst Books.