Geography 4023/5023 Spring 2008
Introduction to Quantitative Methods
Lectures: TR 9:30am – 10:45pm, Chemistry 145
Lab: T 2-4:50pm, Guggenheim 6 (KESDA)
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Instructor: Frank Witmer Guggenheim 201h frank.witmer@colorado.edu OH: TW 11am-12pm (or by appt; Wed in KESDA) |
Teaching Assistant: Ling Shen Guggenheim 312 ling.shen@colorado.edu OH: MT 5-6pm in KESDA (or by appt.) |
Web Page: http://www.colorado.edu/geography/class_homepages /geog_4023_s08
Overview: This course focuses on spatial statistical methods relevant to geographers. The lecture portion of the course focuses on the theoretical underpinnings of the statistics while the lab portion provides the opportunity for students to apply the lecture concepts and techniques. By the end of the course, students are expected to understand introductory spatial statistics and be comfortable using multiple software packages to analyze spatial data. This course satisfies the requirement for quantitative methods for MA and PhD students in Geography.
Prerequisites: Students enrolled in this course must have completed an introductory statistics course (e.g. GEOG 3023, APPM 4570, ECON 3818, PSYC 3101, SOCY 4061, EDUC 5716). Lecture and lab material requires a familiarity with the fundamentals of hypothesis testing, especially t-tests.
Lectures: The lecture portion of the class will present the statistical concepts that form the foundation for lab assignments. Lectures are intended to be an interactive experience, so please do not hesitate to ask a question or make a comment. The more you engage the material, the better you will learn it. Readings must be completed prior to the lecture on the day they are assigned. Please respect your fellow students and me by turning off your cell phones during lecture and lab.
Required Texts:
Bailey, T.C. and A.C. Gatrell (1995). Interactive Spatial Data Analysis. Essex, England, Prentice Hall.
Rogerson, P. (2006). Statistical Methods for Geography. 2nd Edition. London, SAGE Publications.
These texts will be supplemented with additional required readings available from course website.
Other Texts:
Fotheringham, A.S., C. Brunsdon and M. Charlton (2000) Quantitative Geography: Perspectives on Spatial Data Analysis. London, SAGE Publications.
Hamilton, L.C. (1992) Regression with Graphics: A Second Course in Applied Statistics. Belmont, CA, Duxbery Press.
Cressie, N. (1993) Statistics for Spatial Data. New York, John Wiley & Sons, Inc.
Labs: The lab portion of the course will use several commercial software packages including Stata, GeoDa, GWR, and ArcGIS. Lab assignments are due at the beginning of the lab session when the new lab is started. Labs submitted during or after the lab are subject to the 20% late penalty.
Grading: Grades are assigned on the basis of:
2 exams: 40%
Lab assignments: 40%
Research Project: 20%
Late lab assignments up to 1 week late will be downgraded 20%, 100% thereafter. Students must complete all lab assignments to receive a passing grade, even if they are submitted too late to receive any points. No incompletes will be given for the course.
No assignments may be submitted via email.
Honor Code and Plagiarism:
The College of Arts and Sciences has an Honor Code that prohibits plagiarism, cheating, fabrication, aiding academic dishonesty, lying, bribery, and threats at the University of Colorado. A key element of this code is that CU students will not plagiarize which means you may not use someone else’s words, pictures, ideas, or procedures as your own. In some instances, it is appropriate to do so when you provide proper acknowledgement. Cases of plagiarism and violations of the CU Honor Code will not be tolerated. More information can be found online at http://www.colorado.edu/academics/honorcode/, particularly under the “Student Information, What is a Violation?” section.
