This course provides basic statistical tools to identify spatial patterns of social characteristics or economic activities, such as crime, poverty, population or industry. The statistical techniques focus on four main areas of study: the spatial concentration process, the spatial agglomeration process, the identification of conglomerates, and the elaboration of guidelines for decision making. The material for these four areas is articulated in three papers that will be handed in at different times during the semester. Prerequisites. None. A research idea and a georeferenced database are highly desirable.
No textbook is required. Materials will be adjusted and notes will be provided by the instructor, depending on the research interest of the participants.
The design of this syllabus is based on this article here
Outline
1. Plan-elaboration with basic statistics
― Area under the normal curve
― Importance of normalization and other data transformations
― Significance of skewness and normality tests
― Media, standard deviation and z-values
Readings:
Tian, Guangjin, Jiyuan Liu ND Zengxiang Zhang. 2002. Urban functional structure characteristics and transformation in China. Cities, Vol. 19, No. 4, pp. 243–248.
Pareto, Vittorio E. 1992. A Model to Assess Urban Conditions and Dimension Development Projects. Habitat International. Vol. 16. No.4. pp:99-117.
Download material for this section here & a ppt presentation here & here Chebyshev´s theorem here Calculator on line here
2. Median and Exploratory Data Analysis
― Median and Box-plot diagrams
― Modified z-score estimated using the median of absolute deviation about the median (z-MAD)
― Robust normalization of the median (Medcouple and Robust Normalized Boxplot).
Readings:
Lopez, Russ and H. Patricia Hynes. 2003 Sprawl in the 1990s. Measurement, Distribution, and Trends. Urban Aff Rev. January 1; 38(3): 325–355.
Crews, Kelley A. and Manuel F. Peralvo. 2008. Segregation and Fragmentation: Extending Landscape Ecology and Pattern Metrics Analysis to Spatial Demography. Popul Res Policy Rev 27:65–88
Brimicombe, Allan J. 2005. Cluster Detection in Point Event Data having Tendency Towards Spatially Repetitive Events. GeoComputation 2005, 8th International Conference on GeoComputation, Ann Arbor, Michigan
Download material for this section here Data set here
3. Bootstrapping
― Basic concepts. Software: Statkey, Splus and SPSS.
― Bootstrapping the mean. Software: Statkey, Splus and SPSS.
Readings:
Hesterberg, Tim, David S. Moore, Shaun Monaghan, Ashley Clipson, Rachel Epstein, Bruce A. Craig and George P. McCabe (2010), Bootstrap Methods and Permutation Tests, Chapter 16 for Introduction to the Practice of Statistics, 7th edition, by David S. Moore, George P. McCabe and Bruce A. Craig, W. H. Freeman, N.Y.
Download material for this section here
First paper. Spatial concentration process: descriptive statistics and threshold limit values to identify global high values in a case study. A list of some georeferenced variables for your papers here
4. Spatial autocorrelation
Readings:
Instructor’s notes. Installment One. Two. Three. Four. Extra for rates here
Second paper: Spatial agglomeration process: identification of agglomerations in a case study (continuation of the first paper).
5. Overlay analysis with ArcGis 10.2
Ppt presentation here. Students without ArcGis skills have two options:
1. Just describe this third stage and how the final integration of the paper would be, or
2. Make an appointment by email asap for next Tuesday (Nov 18th) so we can meet before class and work together in ArcGis your case study
(be aware I am not a GIS guy).
Readings:
Instructor’s notes.
6. Class classification
Readings:
Galant, K. 2006. Data Classification from Cartographic Point of View Electronic Journal of Polish Agricultural Universities, Geodesy and Cartography, Volume 9, Issue 4. Available Online http://www.ejpau.media.pl/volume9/issue4/art-36.html
Jiang , Bin and Junjun Yin. 2013. Ht-Index for Quantifying the Fractal or Scaling Structure of Geographic Features. Draft at http://arxiv.org/ftp/arxiv/papers/1305/1305.0883.pdf (July 30, 2014).
h/t software available at https://www.dropbox.com/sh/k2aaoip1y888r45/AAACV2jsvP8s0y8a-5reRgrda
Tata, Robert J. and Schultz, Ronald R. 1988. WorldVariation in Human Welfare: A New Index of Development Status, Annals of the Association of American Geographers,78:4,580 — 593
Final paper: Identification of conglomerates in a case study (Integration of two previous papers) and elaboration of guidelines for public policy.
Please do not forget to organize your bibliography in the proper way (APA, MLA, Chicago)
Grading scale
> 93 = A
90 – 92 = A-
87 – 89 = B+
83 – 86 = B
80 – 83 = B-
77 – 79 = C+
73 – 76 = C
70 – 72 = C-
67 – 69 = D+
< 66 = D