Week 9 Agenda

UP206A Git Puller
Welcome to week 8. Concerns? Questions? Stories to share?
Hackathon Part 2
Break
Spatial Analysis: Point Patterns
Who is Eleanor?

Next week’s guest speaker: Albert Kochaphum

Albert is UCLA’s GIS Coordinator, working for the Institute for Digital Research and Education. Notable projects that Albert has managed and developed include the Million Dollar Hoods and Hate Crime Map. Albert is a strong advocate for social justice, open source technologies, and is an alumn from the UCLA Urban Planning Department. Oh, and he can pretty much code up anything he puts his mind into.

Group Assignment #4: Spatial Analysis

This assignment will focus on some of the more advanced spatial analyses techniques learned in class. With one or more datasets you are exploring for your final project, do one of the following:

Find tendencies for spatial clustering in your data by conducting a spatial autocorrelation analysis. Your results must include a global Moran’s I statistic, followed by a local spatial autocorrelation with a moran’s plot that indicates a P-value and a scatterplot with HH, HL, LH, and LL values. Produce a final output in the form of a map that indicates the location of statistically significant spatial clusters.

and/or…

Conduct a thorough point pattern analysis of your dataset. Your notebook should include a KDE plot, as well as a centrography analysis, indicating central tendencies of your data (mean, median, ellipse). Include different “slices” of your data to produce meaningful results (e.g. kde plots for different categorical values).
optionally, you are welcome to explore other spatial analysis approaches not covered in class that you think would better address your research inquiry. Make sure to meet with me with a proposal for an alternative methodology.

Complete your notebook with a markdown cell that succinctly explains the map’s interpretation, what you are visualizing and why it is interesting: tell us its story. This story should be accompanied by any relevant descriptive statistics, as needed, to round out the picture.

At the end of the notebook, include a markdown cell that identifies each group member and describes their contribution to this assignment (one sentence each).

Make sure your notebook runs from the top without any errors and that all the visuals can be seen inline (without me having to re-run your notebook).