STAT260 - Introductory R for Data Science
Course: STAT260 (Introductory R for Data Science) in STAT department at Simon Fraser University.
Credit Hours: 3 • Academic Level: second-year undergraduate course
Course Requirements: Requires 7 prerequisite courses
Prerequisite Chain Depth: 3 levels of foundational courses required
Future Opportunities: Unlocks 8 advanced courses for further study
Interdisciplinary Requirements: Prerequisites span 4 different departments
Course Type: Core pathway course - critical for degree progression
Part of the STAT curriculum at Simon Fraser University, helping students progress through degree requirements.
Courses unlocked by STAT260
- STAT440 - Learning from Big Data
- STAT475 - Applied Discrete Data Analysis
- STAT350 - Linear Models in Applied Statistics
- STAT360 - Advanced R for Data Science
- STAT403 - Intermediate Sampling and Experimental Design
- STAT452 - Statistical Learning and Prediction
- STAT445 - Applied Multivariate Analysis
- STAT485 - Applied Time Series Analysis
Academic Planning at Simon Fraser University
Students planning STAT260 at Simon Fraser University should complete 7 prerequisites before enrollment.
Course Sequence: This course requires a 3-level prerequisite chain, requiring careful multi-semester planning for optimal progression.
Future Pathways: Completing STAT260 enables enrollment in 8 advanced courses, opening specialization opportunities in the STAT program.
This second-year course at Simon Fraser University integrates into structured degree pathways for STAT programs, supporting timely graduation and academic progression.