Research Methods in Geography

Spring, 2007 Syllabus*  

Week

Date

Lecture Topics

Readings

Assignments

Special Notes

1

1/30 ~ 2/2

 Research In Geography: Why Statistics Matters

Review of Descriptive Statistics

R 1

 

 

Last day of add – drop

2

2/6 ~ 2/8

Probability Theory & Discrete Sampling Distributions

R 2

1

Article Review #1 Due (2/8)

3

2/13 ~

2/15

Probability Theory, Discrete Sampling Distributions, & the Central Limit Theorem

R 3

2

 

4

2/20 ~

2/22

& Confidence Intervals & Hypothesis Testing using one sample z-test & t-test

R 4

3

 

5

2/27 ~

3/1

Difference of Means &

Equality of Variance Tests

R 5

4

 

6

3/6 ~

3/8

Data Transformations & Normality Tests

Exam # 1 (3/8)

R 6

 

 

 

7

 

3/13 ~

3/15

Analysis of Variance (ANOVA) , Assumptions & Interpretations

R 7

5

 

 

8

3/20 ~

3/22

No Class, Spring Break!

 

 

 

9

3/27

~

3/29

Correlation  

Bivariate Regression: Assumptions

R 8

6

Last day to withdraw with a “w” 3/30

 

10

4/3 ~

4/5

Bivariate Regression: Interpretations 

Multiple Regression: Assumptions & Interpretations

R 9

7

 

 

11

4/10 ~

4/12

 

Multiple Regression: Model Building  

Categorical Dependent Variables

Logit Regression: Assumptions

R 10

8

 

12

4/17 ~

4/19

Categorical Dependent Variables

Logit Regression: Interpretations 

Exam #2 (4/19)

R 11

 

 

13

4/24 ~

4/26

Non-Parametric Tests of Association Χ­2­

R 12

 

Article Review #2 Due (4/26)

14

5/1 ~

5/3

Measures of Spatial Association &

Spatial Autocorrelation

R 13

9

 

15

5/8 ~

5/10

Spatial Data and Pattern Analysis

R 14

 

 

16

5/15

Measures of Spatial Association &

Cluster Analysis

R 15

 

 

17

5/18 (F)

Final Exam: 11:15 ~ 1:45

 

 

 

 *This schedule should be considered tentative and changes will likely occur throughout the semester.

The Week column lists the week of the semester.  The date for each week is displayed for each Tuesday and Thursday under the Date column.  Notice that the Lecture Topics column lists the topics discussed during lecture.  Approximately each week, I introduce a new statistical approach.

 

The Readings column lists the readings that are assigned for each week and are to be found in your text.  You are responsible for the readings.  In some cases, however, the readings will be derived from handouts that are distributed during class time.  These additional readings will be relevant to the material covered during lectures and will appear on the exam.  I expect that you will read the material as assigned (and not the day before the exam) so as to contribute to in class discussions.  There will also be several short reading handouts distributed in class.  You are also responsible for these handouts for the exams.

 

SMG: Rogerson, Peter. 2001.  Statistical Methods for Geography.  Sage Publications. Thousand Oaks :CA. p. 236.

*************************************************************************************************************************************************************** 

Reading 1

SMG: Chs. 1 & 2

 

Reading 2

SMG: Ch. 3

 

Reading 3

SMG: Ch. 4

Ch. 5, p. 93 - 97

 

Reading 4

SMG: Ch. 5, p. 97 – 105

 

Reading 5

SMG: Ch. 5, p. 105 - 131

 

Reading 6

Ch. 6 “The Problem of Non-normality and Data Transformations” from Matthews, J. 1981. Quantitative and Statistical Approaches to Geography: A Practical Manual. Pergamon Press, Oxford, England.

 

Reading 7

SMG: Ch. 6

 

Reading 8

SMG: Ch. 7

 

Reading 9

SMG: Ch. 8

 

Reading 10

SMG: Ch. 9, 192 - 209

 

Gould, Peter. 1970. “Is Statistix Inferens the Geographical Name for a Wild Goose?” Economic Geography, 46(4):439-448.

 

Reading 11

SMG: Ch. 9, p. 209 – 221

 

Reading 12

Ch. 11 “Goodness-of-Fit and Categorical Difference Tests” from McGrew, J. and Monroe, B. 2000. An Introduction to Statistical Problem Solving in Geography. 2nd Ed. McGraw Hill Boston: MA.

 

Reading 13

SMG: Ch. 10, p. 232 – 243

 

Reading 14

SMG: Ch. 10, p. 222 – 232

 

Reading 15

SMG: Ch. 12

 

Lab Assignment Schedule

The goal of the labs is to provide you with practical experience in formalizing the concepts introduced during the lectures.  The lab topics (listed in the Lab Topic column) are designed to correspond to that week’s lecture.  There are no readings, per se, for the labs.

Lab Topics 

 Assigned Due
1 – Descriptive Statistics and Discrete Probability Dist.  2/8 2/15
2 – Confidence Intervals and Sampling Distributions 2/15 2/22
3 – Hypothesis testing 2/22 3/1
4 – Difference of Means and Equality of Variance Test 3/1 3/9 (Friday)
5 – Analysis of Variance (ANOVA) 3/15 3/29
6 – Correlation and Bivariate Regression 3/29 4/5
7 – Multivariate Regression 4/5 4/12
8 – Logit Regression 4/12 4/20 (Friday)
9 – Spatial Autocorrelation 5/3 5/10