Listed in: Mathematics and Statistics, as STAT-495
Amy S. Wagaman (Section 01)
Our world is awash in data. To allow decisions to be made based on evidence, there is a need for statisticians to be able to make sense of the data around us and communicate their findings. In this course, students will be exposed to advanced statistical methods and will undertake the analysis and interpretation of complex and real-world datasets that go beyond textbook problems. Course topics will vary from year to year depending on the instructor and selected case studies. Potential topics include but are not limited to: visualization techniques to summarize and display high dimensional data, advanced topics in design and linear regression, ethics, selected topics in machine learning and data mining, nonparametric analysis, spatial data, and analysis of network data. Students will enhance their capacity to think and compute with data, undertake and assess analyses, and effectively communicate their results.
How to handle overenrollment: Priority for Statistics majors.
Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: quantitative work, problem sets, quizzes or exams, group work, use of computational software, research paper (project), potential for oral presentations
Section 01
M 10:00 AM - 10:50 AM SMUD 006
W 10:00 AM - 10:50 AM SMUD 006
F 10:00 AM - 10:50 AM SMUD 006
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 |
|---|---|---|---|---|---|---|
| Computer Age Statistical Inference | Cambridge, 2021 | Efron and Hastie | Required; Free pdf of the textbook is available online from the publisher; student edition in print | TBD | ||
| An Introduction to Statistical Learning | Springer, 2021 | James, Witten, Hastie, and Tibshirani | Recommended / Supplemental | TBD |