Zoom Link https://washington.zoom.us/j/96898385387
Welcome to Modern Data Analysis Techniques
Team taught by Miguel Morales (Physics) and Bryna Hazelton (eScience), the goal of this class is to introduce current techniques and best practices in the statistically rigorous analysis of large data sets. The class is organized around four themes: practical statistics, advanced data visualization, building collaborative analysis code, and advanced data analysis practices.
As a graduate elective, what you get out of the course largely depends on what you put into it. Further, this class is designed to scale depending on your interests and time. At one end, it is designed to provide motivated students with a firm grounding in advanced statistics and data analysis tools that can be used on a wide range of academic and professional problems. At the other end it is designed to serve as a low-pressure survey of modern analysis techniques. During the first week you will detail what your goals are, and your grade will be based on how well you achieve your goals. There will be no exams, with the homework and final project forming the basis of your grade.
(Lecture title links to zoom, link to slide pdfs follows. Syllabus still under development, subject to change.)
Homework: Intro quiz
Homework: Homework #1
Homework: HW #2
Homework: HW #3
Th (5/20): Presentations: Michael Pun, Debby Tran, Samantha Tetef
T (5/25): Presentations: Anna Wirth-Singh, Chris Thomas
Th (5/27): Presentations: Samantha Gilbert, Miguel Morales
T: Presentations: Tharindu W. Fernando; Data rampages
Th: Presentations: Rodolfo Garcia, Robert Pecoraro, David Wang
Holding pen (early): example of multi-dimensional probability; multi-parameter distributions, multi-dimensional spaces and triangle plots
Holding pen (late): art of parameters, blind & semi-blind analyses, peer reviewed code.