Course Description:
The primary objective of this course is to familiarize students with a wide variety of analytical
tools used by geographers, so that in your future research/work you will be able to recognize
when a situation calls for some sort of quantitative analysis and have an idea about what sort of
analysis should be performed. Essentially, you are being provided with a toolbox of methods. In
addition to learning techniques and how to apply them, you will also pick up some of the
vocabulary of quantitative geography and develop an ability to critically evaluate quantitative
journal articles and books. An important component of this learning process is good preparation,
and you are expected to read all assignments prior to class.
Course Grading:
- Exercises (40%) -- eight exercises of equal weight (5% each) will be given during the semester.
- Project (35%) -- multivariate analysis with student-collected data; projects are due and student presentations are given in mid-April.
- Exam (25%) -- cumulative, in-class essay exam given during Finals Week.
Grading Scale: A >= 90%, B >= 80%, C >= 70%, D >= 60%, F < 60%
Course Attendance:
- Each unexcused absence from class will reduce your course grade by 5%.
- Each semi-excused absence reduces your grade by 2.5%. Semi-excused absences include: job interviews, more than 2 absences and/or excessive travel to academic conferences, and family functions
(weddings, reunions, etc.).
- More than 10% worth of absence deductions will result in an automatic
failure of the course, regardless of the quality of work and/or the grade you would otherwise receive.
Course Materials: The text is Elementary Statistics for Geographers, 3rd edition, by James E. Burt, Gerald M. Barber, and David L. Rigby. Additional readings are made
available on D2L for student download throughout the term.
Course Schedule:
- Introduction and Review Topics
- Spatial Data Issues
- Spatial Summary Statistics
- Correlation and Regression
- Data Reduction Techniques
- Point and Area Pattern Analysis
- Spatial Dependence and Autocorrelation
- Gravity Models and Spatial Interaction
- Network Connectivity and Accessibility
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Last Updated: 21 December 2011
Oklahoma State University
Department of Geography
Stillwater, OK 74078