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 but will include static and dynamic visualization techniques to summarize and display high dimensional data, advanced topics in design and linear regression, ethics, and selected topics in data mining. Other topics may vary but might include nonparametric analysis, spatial data, and analysis of network data. Through a series of case studies, students will develop the capacity to think and compute with data, undertake and assess analyses, and effectively communicate their results using written and oral presentation.
Requisite: STAT 230, STAT 231, STAT 370, and at least one COSC course numbered 111 or higher, or other computing experience by consent of the instructor. Limited to 20 students. Fall semester. Professor Wagaman.
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), oral presentations
M 9:00 AM - 9:50 AM SMUD 205
W 9:00 AM - 9:50 AM SMUD 205
F 9:00 AM - 9:50 AM SMUD 205
|Computer Age Statistical Inference
|Efron and Hastie
|Free pdf of the textbook is available online from the publisher.