Computational Theory Data Visualization

STA 645-201

Instructor: 
Melissa Q. Pittard
Start Date: 
08/22/22
End Date: 
12/15/22
Semester: 
Fall 2022
Room: 
TBD
Building: 
TBD
Meeting time: 
TBD TBD - TBD
Credits: 
3.0

Course Description

This course aims to teach students to use programming to gain intuition about statistical theory and fundamental concepts and to visualize data appropriately. Specifically, computational methods covered include simulation methods and numerical methods in maximization and integration. Appropriate graphical displays of statistical and simulation results will be emphasized. Statistical concepts covered include sampling distributions, confidence intervals and p-values, the central limit theorem, expectation, and maximum likelihood estimation. Student understanding of course ideas will rely heavily on performing simulation studies and discussing the assimilated class results online.