— Introduction to Statistical Programming
Essentials of statistical computing using a general-purpose statistical language. Topics include algorithms; design; debugging and efficiency; object-oriented concepts; model specification and fitting; statistical visualization; data and text processing; databases; computer systems and platforms; comparison of scientific programming languages.
Topics
- algorithms
- design
- debugging and efficiency
- object-oriented concepts
- model specification and fitting
- statistical visualization
- data and text processing
- databases
- computer systems and platforms
- comparison of scientific programming languages
Topics explicitly listed in official catalogue description
Prerequisites & course information
Course Description: Essentials of statistical computing using a general-purpose statistical language. Topics include algorithms; design; debugging and efficiency; object-oriented concepts; model specification and fitting; statistical visualization; data and text processing; databases; computer systems and platforms; comparison of scientific programming languages. Learning Activities: Lecture 3 hour(s), Laboratory 1 hour(s). Grade Mode: Letter. Learning Activities: Lecture 3 hour(s), Laboratory 1 hour(s). Grade Mode: Letter.
Sources
- Course catalogue ↗2026-2027