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EGeo504
Geographic Methods and Techniques
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INSTRUCTOR
Patrick Buckley, Associate Professor -- Geography
ph. 650-4774
E-Mail patrick@cc.wwu.edu
PRIMARY LEARNING OUTCOME
To prepare program graduate students with the ability to understand, select, apply, and communicate in a highly professional a fashion statistical methods to the solution of real-world problems. That is to broaden and deepen an student's understanding and ability to apply parametric and nonparametric statistical tools to geographic questions.
TEXTBOOKS
Ebdon, David. latest edition. Statistics in Geography. Blackwell: Oxford, U.K. latest edition.
Peter J. Taylor 1977 Quantitative Methods in Geography, Waveland Press: Prospect Heights, IL. (XEROXED -- this is out of print, but we have permission from the author to copy it.)
ADDITIONAL READINGS
Since no one textbook is ever sufficient in statistics other readings may be made available or be suggested for reading throughout the quarter.
Egeo 504 Geographic Methods and Techniques educates students to become:
Effective communicators who...
- Express outcomes of geographic methods and techniques clearly and creatively through the written and spoken word.
- Read and listen critically to descriptions of geographic analysis with understanding and knowledge.
- this will be demonstrated through professionally written assignment/reports and performance on written and oral exams
Literate individuals who...
- integrate learning and apply it to authentic situations.
- begin to read discussions of geographic methods and techniques fluently with comprehension for a variety of purposes.
- develop a strong applied foundation in parametric and non-parametric analytical techniques.
- access, analyze, evaluate and present information using diverse parametric and non-parametric analytical techniques.
- This will be demonstrated through proper application of tools and the ability to read and understand others reports
Critical thinkers and problem solvers who...
- Apply creativity and persistence, and develop awareness of their own thinking, in defining problems and developing strategies to solve them.
- Demonstrate flexibility in thinking.
- This will be demonstrated through problem solving assignemnts
Self-directed, productive learners who...
- Seek personal excellence in applying geographic analytical methods and techniques.
- Independently pursue learning of analytical methods and techniques.
- Set, achieve and reflect on personal and collective goals related to these tools.
- This will be demonstrated through class discussion and assignments.
Constructive community members who...
- Have a clear sense of self and exhibit honesty and integrity in using these tools.
- Work collaboratively and effectively with others in applying these tools.
- Prepare themselves for effective careers in geography.
- This will be demonstrated throughout the class.
CLASS ORGANIZATION
This class is seen as an integral part of a Geography Masters program not because of the statistical tests nor other tools that are used, but rather because of the spatial/geographical manner in which they are applied. A list of techniques to be included in a course of this nature are:
This list is neither meant to be exhaustive nor necessarily the most appropriate set for a given class, but rather a broad illustration of the breadth and depth required.
An Example of how the spatial/geographical would then be emphasized in relation to the above might be as follows:
Issue: Social justice and location of major infrastructure facilities.
Hypothesis 1: There is a relationship between air quality and absenteeism of school children.
Data: Air quality measures and absentee rates of children from school in Los Angeles based on census tracts.
Analytical steps:
1. Using standard mean and deviation based tests, determine if the data is parametric. If this test is met continue.
2. Using parametric Correlation & Regression analysis compare the two variables collected within a defined set of regions to search for first a relationship and second a model of behavior. If this test is met continue.
3. Map out the residuals from the above relationship on a map and then using Spatial Autocorrelation search for significant levels of clustering. If this test is met continue.
4. Using overlay procedures and Coefficient of Areal Correspondence to search for additional explanatory variables to add to the simple bivariate analysis...
Course pace and coverage:
Given the small number of students in the class, and the large variation in their interests, background, and talents, the pace and emphasis of the course will be adjusted to guarantee full understanding by all class members. More gifted students are encouraged to attempt more challenging work, while students less familiar with statistical techniques are coached in providing a thorough and complete analysis of the data and understanding of the technique applied. The course is organized in very much of a seminar style. It is expected that students have already entered the class with a good undergraduate background in statistics, so rather than spending a lot of time again deriving statistical tools, time is primarily spent illustrating their application and usefulness. The philosophy driving the course is that students should be taught how to utilize basic reference materials in understanding a small but not insignificant set of techniques and applications, rather than attempting an exhaustive explanation of numerous techniques. The thought here is that throughout a student's career they will have to teach or re-teach themselves multiple tools, and it is the development of that internal learning process that is most important.
TECHNIQUES
Over the years the following techniques have been covered through a variety of applied exercises:
-Applied spatial probability
-Tests on spatial data utilizing chi-square, kolomogrov-smirnov, difference of means, mann whitney U, Wilcoxon
-Coefficient of areal correspondence, lorenz curve, gini coefficient
-Bivariate correlation and regression
-Nearest neighbor, spatial auto-correlation
In some years, depending on student interests and talents, the following methods were also utilized:
-Factor analysis
-Gravity models
-Quadrat and nearest neighbor analysis
-K-color spatial auto-correlation
In addition to solving the above techniques for applied problems utilizing spreadsheets like Excell, and statistical packages like Statitix and SPSS, some of the output is transferred to GIS formats for display and further analysis.
GRADING
Grading is based on class participation, assignments, and a two part final that includes a written plus oral portion. Throughout the quarter all assignments are graded and returned to students to alert them to the level at which they are performing and areas for improvement. Assignments may require students to locate their own data sets and apply the above techniques to issues in which they have an interest.
Final grades will be based on three parts:
- 10pts for Class preparedness and participation as an active learner
- 60pts for Assignments
- 30pts final, written part (20) and oral part (10)
Letter grades are
- A 100 94
- A- 93 90
- B+ 89 86
- B 85 82
- B- 81 79
- etc... (hopefully no one will be at any lower level)
.