GEOG 705 Spring 2007
Statistical Methods for Geography
Class Hours: Tuesday & Thursday 15:35 16:50
Location: HSS 290 (the Geographic Teaching Lab)
Course Materials: P:\courses\G705\Spring2007
Instructor: XiaoHang Liu (xhliu@sfsu.edu, note there is an "h")
Office Location: HSS 269, 4153387509
Office hours: TH 12:30 – 13:10 & 14:3015:30
Text:
Rogerson, P. Statistical Methods for Geography. Second edition. SAGE Publications (Required).
Software:
1. Student license of ArcView 9.1 with 3 extensions is available free for enrolled students.
2. SPSS installed in HSS 290 and other campus computing labs.
3. MathType 5.2 downloadable from the internet
Course Description:
This course is an introduction to statistical methods for geography. It aims to provide an exposure to classical statistics as well as spatial statistics which can be used to analyze realworld geographical data. Topics progress from descriptive statistics, probability distribution, hypothesis formulation and testing, correlation and regression, data reduction and cluster analysis, to spatial pattern. The goal is to help students understand the utility and assumptions of various statistical methods, to learn how to use statistical package to simplify geographic problem solving, and learn how to apply statistical techniques to real geographical problems.
Materials: Students are required to prepare a USB thumb drive for file transfer and backup.
Methods of Instruction: Lecture, demonstration, laboratory, and discussion. For most assignments, student should plan on working one to two extra hours in addition to the assigned lab time.
Grading and Exams: There will be 10 homeworks, 2 exams, 1 project, and 1 paper discussion. All homework, project, and exams are required to pass this class. All homeworks must be submitted in hard copy on or before the due date. No late submission is accepted!
The course grade will be based on the following allocations: 45% labs, 40% exams, 10% project, 5% paper discussion.
Grading will be on a percentage basis: 10090% A, 8980% B, 7970% C, 6960% D. Plus/minus grades will be assigned for points near the margins. Within the 10090% range, A if both exams are 90+/100, A otherwise.
Incomplete grade is only assigned if the student has completed 75% of the course work AND provided proof of a strenuous situation.
Schedule:
Week 
Dates 
Lecture 
Lab 
Readings

1 
1/25 
Lab 1: Intro. to MathType, due 2/1 
Appendix B  
2 
1/30, 2/1 
Descriptive Statistics 
Lab 2: Descriptive Statistics, due 2/8 
Chapter 1, 2 
3 
2/6, 2/8 
Probability distributions 
Lab 3: Probability distributions, due 2/15 
Chapter 4 
4 
2/13, 2/15 
Hypothesis testing 
Lab 4: Hypothesis testing, due 2/22 
Chapter 5 
5 
2/20, 2/22 
Analysis of Variance 
Lab 5: ANOVA, due 3/1 
Chapter 6 
6 
2/27, 3/1 
Exam I  paper  Exam I  Take home, Due 3/8 

7 
3/6, 3/8 
Correlation and Regression  Lab 6: Correlation and Regression, due 3/15 
Chapter 7&8 
8 
3/13, 3/15 
More on Regression 
Lab 7: Multiple linear regression, due 3/22 
Chapter 9 
9  3/20, 3/22  Data Reduction  Lab 8: Data reduction, due 3/29 
Chapter 12 
10  3/27, 3/29  Exam II  paper  Exam II  take home, due 4/5  
11 
4/3, 4/5  Point Pattern Analysis  Lab 9: Point Pattern Analysis, due 4/19  Chapter 9 
12 
4/10, 4/12  Spring Break, No Class.  
13 
4/17, 4/19 
Area pattern analysis  Lab 10: Area pattern analysis Due 4/26  Chapter 10 
14 
4/24, 4/26 
Project 
Project 

15 
5/1, 5/3 
Project 
project 

16 
5/8, 5/10 
Project Presentation 
Project Presentation 

17 
5/15 
Final Project Due 
Paper discussion: Throughout the semester, each student will lead a 20minute discussion on how statistical methods are used to solve realworld problems. Students can select a paper from the bibliography of the textbook or on their own, and are responsible to acquire and make the paper available to the entire class. Sign up sheet will be distributed in the first class. The title of the selected paper is due in week 2.
Syllabus and schedule are subject to change in the event of extenuating circumstances. Students are responsible to catch up with the announcements and changes. The university policy on plagiarism and disability can be found from SFSU website.