Download GRM 2102 STATISTICAL ANALYSIS IN GEOGRAPHY

GRM 2102
STATISTICAL ANALYSIS IN GEOGRAPHY
2009-2010
Semester One
Lecturer: Prof. Yee Leung ([email protected])
SB 237
Tutors:
FYB 221A 2696 1025
Mr. Zhou Yu ([email protected])
2609 6473
Lecture Venue: ELB LT2 (H3-4)
Course Materials:
[Course Outline]
__________________________________________________________________________
Theme
This course emphasizes fundamental concepts of statistical methods which are applicable to
geographic analysis. Topics covered include elementary probability theory, descriptive
statistics, hypothesis testing, correlation analysis, simple and multiple regression analysis.
Outline
I.
General Background
Developments of Quantitative Analysis in Geography
Ideas of Probability and Statistics
Applications of Probability and Statistics in Geographical Research
II.
Geographic Data and Description
Geographic Data
Describing Geographic Data
III.
Probability Distribution
Probability Density Function and Mass Function
Normal Probability Law
IV.
Concepts of Sampling
V.
Descriptive and Inferential Statistics
Sample mean
Sample variance
VI.
Testing of Hypotheses
Probability Arguments of Hypothesis Testing
Significance Test of Model Parameters and Linear Hypothesis
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VII. Simple Correlation and Regression
Concepts and Estimations of Simple Correlation
Concepts and Estimations of Simple Regression
VIII. Multiple Regression
Concepts of Multivariate Statistics
Concepts and Estimations of Multiple Regression
Expected Learning Outcome
After taking this course, students are expected to be able to (a) understand the basic concepts
in simple statistics that are useful to geographical data analysis, (b) set up the framework for
hypothesis testing with respect to the population mean and difference of population means, (c)
employ probability distributions, particularly the normal distribution to describe data and test
hypotheses, (d) test simple geographical relationships through the concepts of simple
correlation and simple regression.
Learning Activities
There will be lectures, tutorials and homeworks in this course. Lectures emphasize concepts,
computational methods, and illustrations. Tutorials focus on discussion of assigned readings
and materials complementing or substantiating the lectures. Homeworks involve essentially
computational exercises designed to strengthen the understanding of concepts and data
analysis methods. WebCT will be used to facilitate the dissemination of teaching and learning
materials as well as course management.
Assessment
Homework
Tutorial
Mid-term Exam
Final Exam
10 %
10 %
30 %
50 %
2
Feedback for evaluation
In order to improve the teaching and learning quality for this course, the following feedback
mechanisms are implemented.
Feedback
To whom
Where
When
Qualitative feedback from
Tutors and/or teacher
During lecture and
Throughout
students
through informal
outside class
the term
Lecture room
End of the
interaction
Course evaluation
Teacher and department
term
Visiting examiner report
University, department
Overseas
and teacher
Reflection of teacher
Teacher and tutors
(including evidence from
End of the
term
All learning
Throughout
activities
the term
Department
End of the
assessment)
Curriculum review
Related teachers and
Curriculum & Teaching
term
Committee
General References
Barbar, G.M. Elementary Statistics for Geographers. N.Y.: Guilford, 1988.
Burt, J.E. and Barber, G.M. Elementary Statistics for Geographers. N.Y.: Guilford, 1996.
Chao, L.L., Statistics, Methods and Analyses. Tokyo; McGraw-Hill, 1974.
Clark, W.A.V. & P.L. Hosking, Statistical Methods for Geographers. Singapore: Johny Wiley &
Sons, 1986.
Clelland, R.C., J.S. deCani, & F.E. Brown, Basic Statistics with Business Applications. N.Y.:
John Wiley & Sons, 1973.
Daniel, W.W., Applied Nonparametric Statistics. Boston: Houghton, 1978.
Draper, N.R., and H. Smith, Applied Regression Analysis. N.Y.: John Wiley, 1966.
Dixon, C. &B. Leach. Sampling Methods for Geographical Research. CATMOG, No. 17.
Ferguson, R., Linear Regression in Geography. CATMOG, No. 15.
Hammond, R. & P.S. McCullagh, Quantitative Techniques in Geography. London.
Johnston, R.J., Multivariate Statistical Analysis in Geography. London: Longman, 1978.
King, L.J., Statistical Analysis in Geography. N.J.: Prentice-Hall, 1969.
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Larson, H.J., Introduction to Probability Theory and Statistical Inference. N.Y.: John Wiley,
1974.
Maxwell, A.E., Multivariate Analysis in Behavioral Research. London: Chapman and Hall,
1977.
Mendenhall, W., Introduction to Probability and Statistics.
Mass.: Duxburg, 1979.
Spiegel, M.R. Theory and Problems of Probability and Statistics. Schaum’s Outline Series.
Singapore: McGraw Hill, 1980.
Williams, R.B.G. Introduction to Statistics for Geographers and Earth Scientists. London:
Macmillan, 1986.
Specific References:
Key: R=reference
T=tutorial
A=application
M=methodology
Introduction and History
R
Barber, G.M. Elementary Statistics for Geographers. N.Y.: Guilford, 1988.
(Ch.1)
R
Carrison, W.L., “Applicability of Statistical Inferences to Geographical Research”
Geographical Review, 46, pp. 427-29, 1956.
A
Lo, C.P., “Some Aspects of Statistical Geography, “ The Geography Bulletin, No. 8. pp.
R
7-12, 1967.
R
樓恩德, 『統計方法與地理學』 The Geography Bulletin, No.12, pp. 64-73, 1971.
Geographic Data and Description
R
Burt, James E. and Barber, Gerald M., 1996. Elementary Statistics for Geographers,
Section 1.3, 1.4, 2.1-2.3. New York: The Guilford Press. (G70.3. B.37 1996)
R.
McGrew J.C. and Monroe C.B., 1993. An Introduction to Statistical Problem Solving in
Geography, Section 3.1 & 3.2 Dubuque: Wm.C. Brown Publishers (G70.3 M4 1993)
R
Shaw G. and Wheeler D, 1994, Statistical Techniques in Geographical Analysis, 2nd e.d.,
ch. 3, 4.5-4.7. London; David Fulton Publishers (G70.3 S52 1994)
Probability
R
Clelland, R.C., J.S. de Cani & F.E. Brown., Basic Statistics with Business Applications.
New York: John Wiley & Sons. (esp. Ch. 1,3) (HA29 C63 1973)
R
Chao, L.L., Statistics: Methods and Analyses. Tokyo: McGraw-Hill. (exp. Ch.0,2) (HA29
C5425 1974)
R
Burt, James E. Barber, Gerald M., 1996, Elementary Statistics for Geographers, ch. 5.
New York: The Guilford Press. (G70.3 B37 1996)
R
Shaw G. and Wheeler D. 1994, Statistical Techniques in Geographical Analysis, 2nd ed.,
4
Section 5.2, 5.3, 5.4. London: David Fulton Publishers (G70.3 S52 1994)
Describing Spatial Distributions
R
Abler R., Adams J.S. and Gould P. 1971, Spatial Organization: the Geographer’s View of
the World, Englewood Cliffs, N.J.: Prentice hall (G112.A25)
R
Burt, James E. and Barber, Gerlad M., 1996, Elementary Statistics for Geographers,
Section 3.1, 3.2, 3.4. New York: The Guilford Press. (G70.3.B37 1996)
T
Chakravorty, Sanjoy, 1996, A measurement of spatial disparity: the case of
A
income inequality, Urban Studies, 33, 1671-86 (HT 103.U7)
R
Neft D, 1966, Statistical Analysis for Areal Distributions, Philadelphia: Regional Science
Research Institute (G74.N45)
T
Plane, David A, 1997, Measuring spatial focusing in a migration system, Demography, 34,
A251-62 (HB881.A1D53)
R
Shaw G. and Wheeler D, 1994, Statistical Techniques in Geographical Analysis, 2nd Ed,
Section 13.1-13.6.
M
London: David Fulton Publishers (G70.3 S52 1994)
Wong, David W.S., 1997, Spatial dependency of segregation indices, The Canadian
Geographer, 41, 128-36 (G1.C288)
Sampling
R
Barber, G.M., Elementary Statistics for Geographers. N.Y.: Guilford, 1988. (Ch.6)
Testing of Hypothesis
R
Barber, G.M., Elementary Statistics for Geographers. N.Y.: Guilford, 1988. (Ch.7,8,9,
pp.289-303)
R
Chao, L.L., Statistics: Methods and Analyses. Tokyo: McGraw-Hill. Ch.9, 14. (HA29
C5425, 1974)
R
Clark, W.A.V. & P.L. Hosking. Statistical Methods for Geographers. Singapore: John
Wiley & Sons, Ch.7, “ Statistical Inference: Interval Estimation & Hypothesis Testing.” pp.
219-248, Ch.8.1, “Testing Differences of Summary Measures.” pp.249-261, 1986.
R
Larson, H.J., Introduction to Probability Theory and Statistical Inference. N.Y.:John
M
Wiley, Ch.10 (QA 273 L352, 1974).
M
Williams, R.B.G., Introduction to Statistics for Geographers and Earth Scientists. London:
Macmillan, Ch. 11-15, p.123-217, 1986). (G70.3W54)
Correlation and Regression
R
Barber, G.M., Elementary Statistics for Geographers. N.Y.: Guilford, 1988. (Ch.11,
pp.367-377; Ch.12)
R
Ferguson, R., Linear Regression in Geography. CATMOG 15, 1977. (G70.23F47)
R
Clark, W.A.V. & P.L. Hosking, Statistical Methods for Geographers. Singapore: John
Wiley & Sons, Ch.9.2, “The Simple Linear Regression”, pp. 291-331, 1986.
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T
Alexander, J.W., and J.B.Lindberg. “Measurements of Manufacturing: Coefficients of
Correlation,” Journal of Regional Science, 3(1), pp. 71-81, 1961.
T
Knos, D.S., “The Distribution of Land Values in Topeka, Kansas.” In B.J.L. Berry & D.F.
A
Marble, Spatial Analysis: A Reader in Statistical Geography. Englewood Cliffs, N.J.:
Prentice-Hall, pp. 269-89, 1968. (GA9 B53)
M
Williams, R.B.G.
Introduction to Statistics for Geographers and Earth Scientists. London:
Macmillan, Ch.17. The Product-Moment Coefficient of Correlation.” pp.226-257, 1986
(G70.3 W54)
Multiple Regression
TM Clark, W.A.V. & P.L. Hosking, Statistical Methods for Geographers. Singapore: John
Wiley & Sons, Ch.11, “Issues in the Application of General Linear Model”, pp. 365-410;
Ch.12 “Extensions of Multivariate Linear Regression Methods”, pp.413-433, 1986.
M
Draper, N.R. & H. Smith, Applied Regression Analysis. N.Y.: John Wiley, p.9, data: Parts
2.5-2.10, “Multiple Regression Mode”; 3.6-3.11, “Residuals and Durbin Watson Test”; 4.2,
“regression equation”; Ch.6, 1966. (QA 278.2 D7 1981) =DS
M
Edwards, A.L. An Introduction to Linear Regression and Correlation. Part 6.5-6.7,
pp.61-65, and Ch.14, “Multiple Correlation and Regression”, pp. 150-169.
M
Ferguson, R., Linear Regression in Geography. Norwich, England: Geo Abstracts,
CATMOG 15, 1977. (G70.23F47)
A
Greenwood, M.J., “A Regression Analysis of Migration to Urban Areas of A Less-
T
Developed Country: The Case of India”, Journal of Regional Science, 11(2), pp. 253-262,
1971.
T
Hauser, D.P., “Some Problems in the Use of Stepwise Regression Techniques in
Geographical Research”, The Canadian Geographer, 18(2), pp. 148-158, 1974.
M
Johnston, R.J., Multivariate Statistical Analysis in Geography. London: Longman.
“Assumptions of Multiple Regression”, pp. 38-45; Ch.3, “Multiple Correlation and
Regression”, pp.60-68, 1978. (G70.3J65)
M
Maxwell, A.E., Multivariate Analysis in Behavioral Research. London: Chapman & Hall.
Ch.7, “Multiple Linear Regression”, (esp. pp.70-73, 1977). (BF39M36)
M
Yeates, M., An Introduction to Quantitative Analysis in Human Geography. Ch.5, “Multiple
Regression”. 1974. (HF1025.Y4 1974)
M
Thordike, R.M. Correctional Procedures for Research. N.Y.: Gardner Press. Ch.5, “Part
and Partial Correlation”, pp.125-137, Ch.6, “Multiple Regression”, pp.139-173, 1978.
(QA278.2T48. 1978)
M
Williams, R.B.G. Intermediate Statistics for Geographers and Earth Scientists. London:
Macmillan, Ch.27, “The Effects of Major Violations of the Assumptions of the Linear
Regression Model,” pp. 480-530; Ch.29, “Curvilinear Regression,” pp. 554-595; Ch.30,
“Multiple Linear Regression and Correlation,” pp. 596-629, 1986. (G70.3W5)
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