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Course Catalog

140.776.01 Statistical Computing

Department:
Biostatistics
Term:
1st term
Credits:
3 credits
Academic Year:
2017 - 2018
Location:
East Baltimore
Class Times:
  • Tu Th,  1:30 - 2:50pm
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Kasper Hansen
Course Instructor:
  • Kasper Hansen
Resources:
Prerequisite:

140.621 or equivalent

Description:

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:

  1. Install and configure software necessary for a statistical programming environment
  2. Discuss generic programming language concepts as they are implemented in a high-level statistical language
  3. Write and debug programs using R and C
  4. Build and organize a software package with documentation for publishing on the internet
  5. Discuss and implement basic statistical computing algorithms for optimization, linear regression, and Monte Carlo
Methods of Assessment:

Method of student evaluation based on projects

Instructor Consent:

No consent required