Advanced QUANT GEO_6938_Syllabus

Advanced QUANT GEO_6938_Syllabus - GEO 6938(Spring 2012...

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GEO 6938 (Spring 2012) Advanced Quantitative Methods for Spatial Analysis Section: # 5470 (VAR credit, 2 or 3 credit hours) Lectures: T (Tuesdays) à periods 4-6 (10:40AM – 1:40PM) Location: TUR 3012 (Turlington Hall) Instructor: Timothy J. Fik, Ph.D. OFFICE HOURS: Tuesdays: 8:30AM – 10:30AM; and 2:00PM – 3:45PM Thursdays: 12:30PM – 2:45PM; and 4:00PM – 4:45PM Office Location: 3137 Turlington Hall PO Box 117315, Department of Geography, University of Florida Gainesville, FL 32611-7315 (352) 392-0494 [email protected] Pre-requisites The following courses are pre-requisites: GEO 3162c/GEO 6160 -- Introduction to Quantitative Methods for Geographers (or equivalent) and GEO 4167c/GEO 6167 --Intermediate Quantitative Methods (or equivalent). Students must first complete the Intro/Intermediate Quantitative Methods sequence (or its equivalent) and/or must have permission from the Instructor to register for this course or to take this course concurrently with GEO 4167c_6161. Course Description This course surveys selected topics in advanced quantitative analysis and provides a fairly detailed overview of widely used techniques for spatial data analysis. It also provides a series of highly focused discussions on a few of the more popular techniques in spatial statistics and spatial econometric modeling. Emphasis is on the critical examination and analysis of spatial data and point patterns, trend-surface modeling and interpolation, count data modeling, cluster and hot-spot detection, process change statistics in space and time, and spatial regression models. Selected Topics include… Kriging Methods and the Semi-Variogram Selected Topics in Advanced Econometrics (SUR, IV methods, Panel Data Regression) Spatial Econometrics: Spatial Autoregressive and Spatial Moving Average Models Maximum Likelihood Estimation and Model Assessment Inverse Weighting, Kernel Density Methods, and Spatial Interpolation Methods Geographically Weighted Regression (GWR) Poisson Regression and Negative Binomial Regression Data Transformation Techniques to Achieve Normality Cusum and Process Change Statistics Time-Space Clustering Statistics Hot-Spot Analysis (K-functions, Kulldorff, Getis G, Rogerson, etc.)
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Course Components (out of 400 possible points): 1. 2 Lab Assignments (40 points each = 80 points ) – 20% 2. Final Term Project/Paper ( 200 points ) – 50% 3. In-Class Presentation of Final Term Project ( 60 points ) – 15% 4. Class Attendance and Participation ( 60 points ) – 15% [Note that regular attendance is required and attendance will be taken]. Proper classroom etiquette is expected (talking, the use of cell/smart phones, surfing the web, or engaging in any form of social networking is strictly prohibited during lecture… and will not be tolerated). Readings: Recommended and Highly Recommended*
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Advanced QUANT GEO_6938_Syllabus - GEO 6938(Spring 2012...

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