CF6-4 - Mathematical models of uncertainty: Probability and statistics

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Author and Citation Info: 

DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., and Wentz, E. (2006). Mathematical models of uncertainty: Probability and statistics. The Geographic Information Science & Technology Body of Knowledge. Washington, DC: Association of American Geographers. (2nd Quarter 2016, first digital).

Learning Objectives: 
  • Devise simple ways to represent probability information in GIS
  • Describe the basic principles of randomness and probability
  • Compute descriptive statistics and geostatistics of geographic data
  • Interpret descriptive statistics and geostatistics of geographic data
  • Recognize the assumptions underlying probability and geostatistics and the situations in which they are useful analytical tools