##### AM-02 - Analytical approaches

- Compare and contrast spatial statistical analysis, spatial data analysis, and spatial modeling
- Compare and contrast the methods of analyzing aggregate data as opposed to methods of analyzing a set of individual observations
- Define the terms spatial analysis, spatial modeling, geostatistics, spatial econometrics, spatial statistics, qualitative analysis, map algebra, and network analysis
- Differentiate between geostatistics and spatial statistics
- Discuss situations when it is desirable to adopt a spatial approach to the analysis of data
- Explain what is added to spatial analysis to make it spatio-temporal analysis
- Explain what is special (i.e., difficult) about geospatial data analysis and why some traditional statistical analysis techniques are not suited to geographic problems
- Outline the sequence of tasks required to complete the analytical process for a given spatial problem
- Compare and contrast spatial statistics and map algebra as two very different kinds of data analysis

## AM-79 - Agent-based Modeling

Agent-based models are dynamic simulation models that provide insight into complex geographic systems. Individuals are represented as agents that are encoded with goal-seeking objectives and decision-making behaviors to facilitate their movement through or changes to their surrounding environment. The collection of localized interactions amongst agents and their environment over time leads to emergent system-level spatial patterns. In this sense, agent-based models belong to a class of bottom-up simulation models that focus on how processes unfold over time in ways that produce interesting, and at times surprising, patterns that we observe in the real world.