Instructor: Pat Bartlein, 541-346-4967, OH: 3-4pm Weds.
GE: Kate Shields, OH: 12-1 pm Weds., 10-11am Fri.

1 Course objectives

Phenomena describable by multiple variables arise in many subfields of physical and human geography and related disciplines. The focus of this course is on the analysis and display of multivariate geographical data by traditional multivariate “machine-learning” methods and by newer methods of scientific visualization.

2 Topics covered

The specific topics that will be examined include:

3 Schedule – Winter 2021

See the Canvas course web page for Assignments and Quizzes

Lec Day Date Topic – see individual webpages for readings Exercises (F) Quizzes (M)
=== === ====== ===================================== ========== =========
1 Tu Jan 5 Intro, data analysis and visualization in R
2 Th Jan 7 Univariate plots 1 Jan 8
3 Tu Jan 12 Bivariate plots  
4 Th Jan 14 Descriptive statistics 2 Jan 15
5 Tu Jan 19 Multivariate plots
6 Th Jan 21 Graphics with ggplot2 3 Jan 22
7 Tu Jan 26 Maps in R 1 Jan 25
8 Th Jan 28 Geospatial analysis in R 4 Jan 29
9 Tu Feb 2 Data wrangling and matrix algebra
10 Th Feb 4 Reference distributions
11 Tu Feb 9 Statistical inference         2 Feb 8
12 Th Feb 11 Analysis of variance         5 Feb 12    
13 Tu Feb 16 Regression analysis        
14 Th Feb 18 More regression analysis         6 Feb 19
15 Tu Feb 23 Nonparametric regression         3 Feb 22        
16 Th Feb 25 Principal components and factor analysis 7 Feb 26
17 Tu Mar 2 MANOVA, discriminant analysis
18 Th Mar 4 Multivariate distances and cluster analysis
19 Tu Mar 9 High-resolution and high-dimensional data sets
20 Th Mar 11 Analysis and visualization of large raster data sets 8 Mar 12 4 Mar 15

4 Grading and course mechanics

Format and grading: Lectures, four quzzes, and eight exercises. The eight exercises will be worth eight points each, and the four quizzes will be worth nine points each, for a total of 100 points. Students taking GEOG 595 will be required to submit a short (3-5 page, plus figures) analysis of a “real” data set. All quizzes and all exercises must be completed to receive a passing grade for the course. The quizzes and exercises should be completed in a timely fashion, although this quarter allowances will be made. Grading expections will be adjusted to reflect the nature of the course this year.

Office hours will be conducted through Zoom.

Prerequisite: GEOG 4/581 GIScience I (or GEOG 4/516 Introductory Geographic Information Systems)

Expected effort: “Lectures” will probably take around an hour to view, but it would be good to send additional time replicating the demonstrations in R and RStudio. Exercises will require around 4 hours each for completion; more or less time may be required depending on the efficiency with which they are done. Plan on spending about 4 hours per week on reading and reviewing class web pages and notes. In addition a few hours may be required for downloading and setting up R.

Other topics: As is implied by the topic of the course, the visual inspection and interpretation of the output of computer analyses will be important, but accommodation for alternative methods of course-material access may be possible–please see me a soon as possible. Collaboration on the exercises is not prohibited (and in fact is a good idea) but the answers must be composed individually. Similarly, discussion of the exam questions may be useful in forming answers, but again, the answers must be composed individually.

Academic Misconduct: The University Student Conduct Code (available at defines academic misconduct. Students are prohibited from committing or attempting to commit any act that constitutes academic misconduct. By way of example, students should not give or receive (or attempt to give or receive) unauthorized help on assignments or examinations without express permission from the instructor. Students should properly acknowledge and document all sources of information (e.g. quotations, paraphrases, ideas) and use only the sources and resources authorized by the instructor. If there is any question about whether an act constitutes academic misconduct, it is the students’ obligation to clarify the question with the instructor before committing or attempting to commit the act. Additional information about a common form of academic misconduct, plagiarism, is available at:

Also, the support provided by the following may be useful: