Instructor(s): Chris Chizinski
Number of Credit Hours: 3
Cross-listings: None.
Prerequisites: Graduate standing is required.
Description: Vector and quadtree data structures, use of relational database management systems, topologically structured databases, query languages, digital terrain modeling, advanced data analysis methods and research issues in GIS. Extensive practical experience with the current GIS software.Implement best practices for scientific computing. Practice with a scientific workflow from the design of the sampling scheme, through generation of the data in the field or lab, up to the point of analysis. Understand cognitive constraints on visualization. Use modern software tools to produce publication quality data visualizations.
Learning Outcomes/Course Objectives
- Demonstrate an ability to identify appropriate statistical procedures suited for a research question.
- Use appropriate techniques to develop, conduct, and analyze a wide range of data.
- Demonstrate sound reproducible coding skills.
- Assemble results into publication quality graphics and tables.
- Assemble computing skills to solve real world problems.
- Examine potential for generalization and transferability of analysis outcomes.