An introduction to the nature of geographic data and organization, descriptive spatial statistics and inferential statistics.
|Two lectures, one lab (two hours); one term
|Prerequisite(s): One of EARTH SC 2GI3 (GEO 2I03), ENVIR SC 2GI3, GEOG 2GI3
|Cross-List(s): EARTH SC 2MB3, GEOG 2MB3, ENVIR 2MB3
|Antirequisite(s): ECON 2B03, SOC SCI 2J03
Time/Term Offered: Term Two, Winter 2012-13
Instructor: Dr. Bruce Newbold
Room: General Science Building Rm. 206/B
Tel:(905) 525.9149 x27948
Office hours: Wednesdays, 1:00 – 2:00 (Or by appointment. To book an appointment, please contact Ann Wallace (firstname.lastname@example.org) to book.)
Instructional Assistant: Patrick DeLuca
Room: BSB 342/B
Tel: (905) 525‐9140 ext. 27786
Office hours: Tuesdays, 10:30 – 12:30 (or by appointment)
Charles Burke Email: email@example.com
Ryan Kelly Email: firstname.lastname@example.org
Chris Higgins Email: email@example.com
The course is meant to provide a strong foundation in spatial and aspatial statistics. The emphasis will be on the most common methods, including descriptive statistics, exploratory techniques, analysis of categorical data, and fundamentals of regression. Completion of the course will enable students to:
• Understand geographic data and its organization, descriptive and inferential statistics
• Describe and discuss the main elements of the above methods and techniques.
• Understand the basic concepts of descriptive spatial statistics
• Correctly identify different types of spatial data, and to select appropriate analytical methods and techniques.
• Apply a variety of statistical methods and techniques to geographical data
• Acquire skills in using a variety of computer packages including: Spotfire S+, ArcGIS, CrimeStat and GeoDA.
• Interpret statistical results obtained through the application of statistics to geographical problems and to support your interpretation with articulate descriptions of a spatial process.
• Demonstrate sound geographical problem-solving skills.
Please consult table for lecture and lab locations and times. Attendance in both are mandatory, and the TAs
will take attendance each week in the lab.
Required Text Books/Course materials:
The required text for the course is:
McGrew J.C. and Monroe C.B. (2000) An Introduction to Statistical Problem Solving in Geography, 2nd Edition. Waveland Press Inc, Long Grove, Illinois. ISBN 978-1-57766-633-2
You are expected to consult the above text for treatment of statistical principles, techniques and applications covered in class. The schedule of readings is included in the Course Schedule. To make the most of your experience, you should read this material prior to coming to class.
Resources for Completing Labs
A workbook is available that introduces the computing environment, including an introduction to Spotfire S+ 8.2 as well as Microsoft Excel, and ArcGIS 10.1. It contains step-by-step examples of analysis for all the methods and techniques covered in class, using real world data sets, and are available on a cost recovery basis ($15).
Avenue to Learn
A website has been developed for this course using Avenue to Learn — a powerful course management tool. All registered students are automatically enrolled in the website, which can be accessed at the following web address:
The steps for logging into the website are as follows. In the LOG INTO Avenue to Learn box, click on the ‘McMaster e-Learning’ link. A new box will appear that will prompt you for your MAC ID and PASSWORD. Finally, click on the SUBMIT button. You should now be in your Avenue to Learn home page. All courses you are enrolled in that make use of Avenue to Learn will appear on this page. To enter a specific course, click on the course name.
Exercises (1 @ 5%; 5 @ 9%) 50 %
Midterm : 15 % (February 27, in class)
Final examination (Cumulative): 35 % (During examination period)
Total: 100 %
Academic dishonesty consists of misrepresentation by deception
or by other fraudulent means and can result in serious consequences,
e.g. the grade of zero on an assignment, loss of credit with a notation
on the transcript (notation reads: “Grade of F assigned for
academic dishonesty”), and/or suspension or expulsion from the
The following illustrates only three forms of academic dishonesty:
Plagiarism, e.g. the submission of work that is not one’s
own or for which other credit has been obtained.
Improper collaboration in group work.
Copying or using unauthorized aids in tests and examinations.
It is your responsibility to understand what constitutes
academic dishonesty. For information on the various kinds of academic
dishonesty please refer to the Academic Integrity Policy, located at http://www.mcmaster.ca/policy/Students-AcademicStudies/AcademicIntegrity.pdf
The instructor and university reserve the right to modify elements of the course during the term. The university may change the dates and deadlines for any or all courses in extreme circumstances. If either type of modification becomes necessary, reasonable notice and communication with the students will be given with explanation and the opportunity to comment on changes. It is the responsibility of the student to check their McMaster email and course websites weekly during the term and to note any changes.