Listed in: Mathematics and Statistics, as STAT-231
Katharine F. Correia (Section 01)
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: $100 ?
Section 01
Tu 01:00 PM - 02:20 PM WEBS 102
Th 01:00 PM - 02:20 PM WEBS 102
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.
ISBN | Title | Publisher | Author(s) | Comment | Book Store | Price |
---|---|---|---|---|---|---|
Modern Data Science with R | Boca Raton, FL: CRC Press, 2017 | Baumer, Benjamin S., Daniel T. Kaplan, and Nicholas J. Horton | Required | Amherst Books | TBD | |
Using R and RStudio for Data Management, Statistical Analysis, and Graphics | Boca Raton, FL: CRC Press, 2015 | Horton, Nicholas J. and Ken Kleinman | Recommended | TBD |
These books are available locally at Amherst Books.