Uncertainty

FC-26 - Problems of scale and zoning
  • Describe the concept of ecological fallacy, and comment on its relationship with the MAUP
  • Describe the MAUP and its affects on correlation, regression, and classification
  • Describe the modifiable areal unit problem (MAUP) associated with aggregation of data collected at different scales and its affect on spatial autocorrelation
AM-87 - Problems of currency, source, and scale
  • Describe the problem of conflation associated with aggregation of data collected at different times, from different sources, and to different scales and accuracy requirements
  • Explain how geostatistical techniques might be used to address such problems
AM-86 - Theory of error propagation
  • Describe stochastic error models
  • Exemplify stochastic error models used in GIScience
AM-85 - Propagation of error in geospatial modeling
  • Compare and contrast error propagation techniques (e.g., Taylor, Monte Carlo)
  • Explain how some operations can exacerbate error while others dampen it (e.g., mean filter)
FC-26 - Problems of scale and zoning
  • Describe the concept of ecological fallacy, and comment on its relationship with the MAUP
  • Describe the MAUP and its affects on correlation, regression, and classification
  • Describe the modifiable areal unit problem (MAUP) associated with aggregation of data collected at different scales and its affect on spatial autocorrelation
FC-25 - Error
  • Compare and contrast how systematic errors and random errors affect measurement of distance
  • Describe the causes of at least five different types of errors (e.g., positional, attribute, temporal, logical inconsistency, and incompleteness)
FC-24 - Definitions within a conceptual model of uncertainty
  • Describe a stochastic error model for a natural phenomenon
  • Differentiate between the following concepts: vagueness and ambiguity, well defined and poorly defined objects, and fields or discord and non-specificity
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
AM-87 - Problems of currency, source, and scale
  • Describe the problem of conflation associated with aggregation of data collected at different times, from different sources, and to different scales and accuracy requirements
  • Explain how geostatistical techniques might be used to address such problems
AM-86 - Theory of error propagation
  • Describe stochastic error models
  • Exemplify stochastic error models used in GIScience
AM-85 - Propagation of error in geospatial modeling
  • Compare and contrast error propagation techniques (e.g., Taylor, Monte Carlo)
  • Explain how some operations can exacerbate error while others dampen it (e.g., mean filter)

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