140.776.01
Statistical Computing
Location
East Baltimore
Term
1st Term
Department
Biostatistics
Credit(s)
3
Academic Year
2019 - 2020
Instruction Method
TBD
Tu, Th, 1:30 - 2:50pm
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Roger Peng
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
140.621 or equivalent
Covers practical issues in statistical computing. Includes programming in R, calling complied code from R, accessing R libraries, creating R packages with documentation, debugging, organizing and commenting code. Topics in statistical data analysis and optimization provide working examples.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Install and configure software necessary for a statistical programming environment
- Discuss generic programming language concepts as they are implemented in a high-level statistical language
- Write and debug programs using R and C
- Build and organize a software package with documentation for publishing on the internet
- Discuss and implement basic statistical computing algorithms for optimization, linear regression, and Monte Carlo