GEO 310
QUANTITATIVE METHODS IN GEOGRAPHY
CB 209 Tue,Thur 2:00-3:15PM
Tel. 257-1276
FALL, 2005
Prof T R Leinbach
1477 Patterson Tower
e-mail:leinbach@uky.edu
Course Description
Quantitative Methods in Geography will be composed of lectures, discussions and exercises and
is designed as an undergraduate level introduction to spatial analysis and the application of
statistical methods in a spatial context. The focus is on the development of a working knowledge
of statistical and quantitative techniques and the application of these to geographic data sets.
Emphasis will be placed upon sound practices in data acquisition, the development of problem
structures, and the evaluation and interpretation of solutions. There will be occasional discussions
in class of particular techniques as applied in the published geographical literature.
The course will allow everyone to learn and develop skills in the use of SPSS 13 (Statistical
Package for the Social Sciences) software. Numerous sessions will be held in a laboratory
environment so that familiarity with the software can be gained in class.
Grades will be determined by the completion of a set of exercises which stress application of the
techniques. In addition, two examinations will be given, one at the mid-term and another in the
final exam period. Occasional quizzes are possible. See the following url for assistance in
computing assistance: http://www.uky.edu/ComputingCenter/SSTARS/
REQUIRED TEXT: J Chapman McGrew and Charles Monroe, Statistical Problem
Solving in Geography, McGraw-Hill, 2nd edition, 2000.
OPTIONAL TEXT: Marija J Norusis, SPSS 12.0 Statistical Procedures
Companion, Prentice-Hall, 2003
https://www.uky.edu/ComputingCenter/SSTARS/- see especially the SPSS manuals and
SPSS and documentation
COURSE OUTLINE:
I. The Use of Statistical Methods in Geography
A. What is Spatial Analysis?
B. Measurement Levels and Spatial Data
C. Measures of Central Tendency and Dispersion
D. Other Descriptive Measures
E. Exploratory Data Analysis
Suggested Readings: McGrew and Monroe, Chapter 1, 2, 3; Burt and Barber, Chapters 1 and
2.
For an introduction to SPSS and data files, preparation and set up see, Norusis, Chapters 1,
2, 3, 4, 5, 6
II. Measures of Spatial Distributions
A. Types of Spatial Data
B. Point Distributions
C. Line Distributions
D. Discrete Areal Distributions
E. Spatially Continuous Distributions
Suggested Readings: McGrew and Monroe, Chapter 4; Burt and Barber, Chapter 3; Hammond
and McCullagh, Chapter 2
III. How Do We Use Probability in Problem Solving
A. Elementary Probability Theory
B. Random Variables and Probability Distributions
C. Normal Distribution
D. Binomial Distribution
E. Poisson Distribution
F. Baye's Theorem
Suggested Readings: McGrew and Monroe, Chapter 5; Burt and Barber, Chapter 5, 6
IV. Spatial Sampling and Sample Estimates
A. Why is Sampling Important and Necessary?
B. Steps in the Sampling Process
C. Types of Samples
D. Clustering and Sampling Frames
E. Areal Sampling
F. Non-probability Sampling
Suggested Readings: McGrew and Monroe, Chapter 6 and 7; Burt and Barber, Chapter 7
V. Testing Hypotheses in a Geographic Context
A. Point and Interval Estimation
B. Key Steps in Testing Hypotheses
C. PROB-VALUE Method of Hypothesis Testing
D. Statistical Significance
E. Two Samples: The t Test
F. Analysis of Variance (ANOVA) (Norusis, Chapter 7, 8, 9)
Suggested Reading: McGrew and Monroe, Chapter 8, 9, 10; Burt and Barber, Chapters 8,9,10
VI. The Use of Non-parametric Tools in Spatial Analysis
A. How Do Parametric and Nonparametric Techniques of Analysis Differ?
B. Comparing Groups
1. Sign Test
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2. Mann-Whitney
3. Kruskal-Wallis
C. What Do We Mean By: Goodness of Fit Tests (Norusis Chapter 10)
1. Chi-Square
2.Kolmogorov-Smirnov
D. Contingency Tables
Suggested Readings: McGrew and Monroe, Chapter 11 ; Burt and Barber, Chapter 11
VII. Introduction to Correlation Analysis
A. Product Moment Correlation
B. Non-Parametric Correlation
C. Areal Association
D. Spatial Autocorrelation
Suggested Reading: McGrew and Monroe, Chapter 13 ; Norusis, Chapter 11; Burt and Barber,
Chapter 12
VIII. Introduction to Regression Analysis
A. Simple Linear Model
B. Estimation Procedures: Ordinary Least Squares (OLS),etc.
C. Interpretation of the Equation
D. Spatial Interpretations of Residual Analyses
E. Technical and Methodological Issues
F. Multiple Regression Models in Spatial Context
G. Non-linear Models: Trend Surface Analyses
Suggested Readings: McGrew and Monroe, Chapter14; Norusis, Chapter 12; Burt and Barber,
Chapters 13, 14
ADDITIONAL RESERVE READINGS
A Stewart Fotheringham, Chris Brunsdon , Martin Charlton. Quantitative Geography. Sage,
2000. G70.3 .F68
R. Hammond and P. McCullagh. Quantitative Analysis in Geography.
Oxford, 2e, 1978. G70.3 .H35 1978
Marija J Norusis, SPSS 12.0 Statistical Procedures Companion, Prentice-Hall, 2003
Larry O’Brien. Introducing Quantitative Geography: Measurement, Methods and Generalized
Models. Routledge, 1992 G70.23 .O36 1992
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