Advanced Spatial Statistics Dr. Kenneth M. Hinkel
(15-Geog-586) 400F
Braunstein Hall
Winter,
2005 556-3430
12:00-12:50
MWF Office
Hrs: 11-12 MWF
e-mail:
Kenneth.Hinkel@uc.edu TA:
Course
Description/Objectives: This course deals with
understanding the application of spatial statistics in human and physical
geography, and in the earth sciences.
Emphasis is placed on concepts, problem formulation, interpretation of
statistical software output, and analyzing mapped patterns.
Grading: (Tentative) 30% Midterm Exam
40% Labs and Quizzes
30% Final Project
Textbook: An Introduction to Statistical
Problem Solving in Geography, 2nd Edition, by McGrew and Monroe. McGraw Hill, 2000.
Tentative Schedule: It may be necessary to modify the schedule.
|
Lect
# |
Date |
Topics Covered |
Assi: |
|
1 |
M: 1/3 |
Intro: Purpose of course, |
Chapt 1&2 (end week); data set 7wks. |
|
2 |
W: 1/5 |
Go over Chi-Sq method, bins, stats, show how to do by hand and spreadsheet, show NCSS and prob calculator |
|
|
3 |
F: 1/7 |
Table X2 and vars: go over Wed again, more detail, sorting, cover use of DescStats MAAT in NCSS, histo, Type I and II |
|
|
4 |
M: 1/10 |
X2 results from each variable; NCSS analysis of same and interpretation of results; t-tst sample and mu; dividing prec up by first 50 and 2-sample t-test; dividing up using random numb generator and compare results. Assi: Manual Chi sq new var 8 bins, analyze divided Elev sample for 2-sample t-test |
Chapt 3, 5, 7 (to p103), end week |
|
5 |
W: 1/12 |
Cover ManChi with 8 bins, elev 2sample t-test. Lecture 2: Covariation, correlation coeff, examples weak vs. strong. Do same in NCSS with corr and matrix, scatter diagram matrix. Discuss MapViewer centroid, data file development. |
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6 |
F: 1/14 |
25 min: Quiz 1 (grade at home). Concept of least squares, r2, slope and intercept, SEE, example snowfall |
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|
7 |
M:1/17 |
No class: MLK |
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8 |
W:1/19 |
Continue: Total, expl, unexpl var, residuals, curves and curve fitting; NCSS for LakeSnow output), MAAT and Lat, Prec and Lat, Return Quiz 1. |
Chapt 8, 9, 10 & 11 |
|
9 |
F:1/21 |
Ocean Crust, Metropolis and curve fitting. Mult reg PPT (3), demo with MapView (midwest), Surfer, plane fitting. |
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|
10 |
M:1/24 |
Continue, prec lat, long. See A,B,C. Demonstrate concordance with Surfer, mapping and residuals of planar fit to prec. Quiz 2, take home. |
Chapts 13 & 14 |
|
11 |
W:1/26 |
Finish multiple with D. Then multicolinearity, mult var analy, stepwise reg |
|
|
12 |
F:1/28 |
Go over Quiz 2. Demo with elev. Do same with Discharge data set from Quiz 1. |
|
|
13 |
M:1/31 |
Go through Surfer and NCSS, lab day |
|
|
14 |
W:2/2 |
Discuss choropleth maps, OhioAccidents, multiple regression |
|
|
15 |
F:2/4 |
Mid-Term |
4, 12 |
|
16 |
M:2/7 |
Review exam. Lecture 5: Time/spatial series analysis: filtering (smoothing and amplifying), 1- and 2-d, EW-42N and 110to 120 |
6, 7 sampling |
|
17 |
W:2/9 |
Continue example in Grapher, running vs weighted averages, autocorrelation and SSP, components of spatial var. |
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|
18 |
F:2/11 |
Guest: Wolf Roder: Contingency analysis |
??? |
|
19 |
M:2/14 |
Power spectra & Fourier transforms, examples, begin Lecture 6: mean center and weighted mean center (USCentroid2000), |
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|
20 |
W:2/16 |
Cont with example, same with area weighted mean, sampling strategies, nearest neighbor stat, finish Lect 6. |
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|
21 |
F:2/18 |
Surfer output of NNS, test of randomness, Quiz 3. HAND IN FINAL PROJECT MATERIALS |
All books chapts done |
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22 |
M:2/21 |
Guest: |
??? |
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23 |
W:2/23 |
Guest: |
??? |
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24 |
F: 2/25 |
Guest:
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??? |
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25 |
M:2/28 |
Student presentations of data analysis |
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26 |
W:3/2 |
Student presentations of data analysis |
|
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27 |
F: 3/4 |
Student presentations of data analysis |
|
|
28 |
M:3/7 |
Student presentations of data analysis |
|
|
29 |
W:3/9 |
Student presentations of data analysis |
|
|
30 |
F:3/11 |
Student presentations of data analysis |
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