Site Navigation

Section Navigation

Courses : Syllabi : 585

Geography 585 Quantitative Methods in Geographic Research

Instructor

Dr. Li An

Course Description

This course introduces concepts and techniques of a set of quantitative methods, emphasizing their applications in geographic research. Quantitative methods have connections to many fields (such as ecology, commerce, marketing, and redistricting of political jurisdictions) and your daily life. Using several San Diego related spatial datasets (rather than lifeless numbers alone), we will explore questions, test hypotheses, and solve problems throughout the course, aiming to achieve the following goals:

Computational resources: Though this course is not specifically designed for software training, participants are encouraged to get your hands wet to explore the powerful capacities of SAS and ArcGIS in geographic data processing and analysis. These two software packages are available in all the SAL and CESAR computers.

Conduct: Attendance and attentiveness in class pays off on your home assignments and exams. Reading materials (e.g., newspapers) or other distracting behavior during class will not be permitted. Lateness to class disrupts the activities and is not appreciated by either the instructor or your fellow students. You are responsible to know the elements of, and penalties for, academic misconduct, including dishonesty, plagiarism, cheating, etc. The penalty for violating these SDSU policies in this class is an “F” for the exam, assignment, or in-class work where the violation occurs.

Other notes: Students with disabilities should talk to me for any possible facilities or assistance. Go to http://www.sa.sdsu.edu/dss/dss_home.html for more information. By the end of the second week of classes, students should notify the instructor of planned absences in this class for religious observances.

Prerequisites

All participants are expected to have taken either GEOG 385 (Spatial Data Analysis) or a course in probability and statistics, or have the working knowledge of the materials presented in these two courses. Otherwise, seek permission from the instructor.

Grading

Your scores of the class (1000 points) will be comprised of the following components:

Lateness: All the assignments should be turned in on time. Late assignments will be docked 20% per day, beginning effective on the due date, unless a pre-permission is granted from the instructor for special reasons such as sickness. Lateness over three days will not be accepted. The valid excuses for missing the exam or failing to turn in an assignment on time are illness requiring medical care, university responsibilities, or personal emergency of a serious nature. Documentation is required, or permission from the instructor. Excuses such as a time conflict, oversleeping, and forgetting are not accepted. In case that a makeup exam is justified and needed, contact the instructor as soon as possible.

Books and Materials

Required text: A bound collection of chapters from multiple sources, available at Montezuma Publishing, around $50 each.

Optional text: Statistical Methods for Geographers (Clark and Hosking 1986, John Wiley & Sons: New York. ISBN 0-471-81807-0), available at SDSU bookstore; you can also buy online (e.g., amazon.com) at a possibly lower cost.

Weekly Topics

Week Topic
Week One Intro to class
Week Two Data and Intro to SAS & GIS
Computation in SAS and Excel
Visualizing data I
Week Three Visualizing data II
Descriptive statistics
Week Four Statistical inference
Week Five Statistics for spatial data
Spatial autocorrelation
Week Six Spatial autocorrelation
Simple regression analysis
Week Seven Simple regression analysis
Matrix algebra
Week Eight Midterm One
Multiple regression analysis
Week Nine Issues in MRA
Extensions of MRA
Week Ten Advanced topics in MRA
Logistic regressions I
Week Eleven Logistic linear regressions II
Logistic linear regressions III
Week Twelve Midterm Two
Geographically weighted regressions (GWR) I
Week Thirteen Geographically weighted regressions (GWR) II
Week Fourteen Cluster analysis)
Factor analysis
Week Fifteen Review for Final Exam

The statements found on this page/site are for informational purposes only. While every effort is made to ensure that this information is up to date and accurate, official information can be found in the university publications.