Course

Course Summary
Credit Type:
Course
ACE ID:
STAT-0058
Organization's ID:
640
Organization:
Location:
Online
Length:
4 weeks
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 1 Geospatial Statistics
Description

Objective:

The course objective is to teach students about the relationship between maps and the data they represent, and how such data are coded in the R environment. Students explore point pattern analysis, spatial autocorrelation statistics, and geostatistical interpolation to estimate values across a continuous contour type map.

Learning Outcomes:

  • Use gstat to analyze continuous field data and create contour maps.
  • Use spastat to analyze patterns in point data and detect non-randomness.
  • Use spdep to analyze patterns in area data and measure spatial autocorrelation in lattice data.
  • Describe and implement the ways spatial data is represented in R.
  • Describe spatial data using maps.

General Topics:

  • Spatial Data and Maps
  • Ways Spatial Data is Represented in R
  • Patterns in Point Data, Non-randomness, spastat
  • Patterns in Area Data, Measuring Spatial Autocorrelation in Lattice Data, spdep
  • Continuous Field Data, Contour Maps, gstat
Instruction & Assessment

Instructional Strategies:

  • Discussion
  • Practical Exercises
  • Textbook readings

Methods of Assessment:

  • Other
  • Capstone case study project, graded practical exercises, and discussion forums

Minimum Passing Score:

80%
Supplemental Materials