Welcome to QERM 598: Special Topics

(this is an archive of the Winter 2007 QERM 598 class)

("qerm" is the wiki-wide password)

The Course

• This is a course designed to fill in first year QERM students (and possibly interested outsiders from Forestry and Fisheries) on some applied statistics and modeling techniques using R. The official course name is: Applied Statistical Methods and R. This has trumped the original tentative name for the course, which was: Accelerated Introductory Applied Statistics and Modeling with an Ecological and Resource Management Flavor (Relying Heavily on R), or AIASMERMF(RHR) for short.

• The winter 2007 course will be coordinated and organized by Eli Gurarie and Mike Keim, but is intended to be very much a collaboration. This wiki is freely editable: the password is "qerm". The course will meet once a week (mostly) on Monday afternoons and will be taught by interested QERM students and faculty. It will be a 2 credit hour Pass/Fail course.

• Each week will consist of a lecture, an R lab and an assignment. One of the practical goals is to create a body of labs, assignments and datasets that can be used as a basis for a continuation of this course in years to come. All of these materials will be stored on this wiki.

• Rather than emphasize the mechanics of doing various statistical analyses, the goal of the course is to develop the ability to use computational tools creatively to help visualize and grasp statistical concepts and modeled processes. There will be lots of emphasis on simulation since this is such an important tool in practise but rather scantily touched upon in courses. As the course progresses, R skills will be acquired, but R itself is not subject of the course.

Syllabus

Here is a syllabus. Because of the informality of the environment, there is a lot of flexibility in the structure.

• Weeks 1-3 (Mike - with some LaTeX from Bert) Distribution functions and simulating data from distributions plus an introduction to R: defining and manipulating objects, using functions, plotting, loops. Comparison tests: T-tests, paired comparisons, non-parametric tests (Rank and randomization tests). Again emphasis on simulation.

• Weeks 4-5 (Eli) Analysis of Variance theory and implementation in R: single-factor, fixed-effect balanced designs. Formulation of statistical models.

• Weeks 6 (Eli) Simple linear regression, theory and implementation in R. Relationship to ANOVA, more on statistical models and parsimony.

• Week 7 (Loveday) Chi-squared contingency tables.

• Week 8-9 (Eli) Simulating ecological processes, population dynamics, movement, stochastic modelling.

• Week 10 (Ian et al.) Examples of fancier R Stuff (maps, colors, surface/contour plots). Student presentation and workshop on stochastic models.

Meeting times and locations

• Odegaard Undergraduate Library (OUGL) Computer Lab 102 (3:30-4:50)**

• January 8
• January 15 - HOLIDAY (room was not available on Wed., Jan. 17).
• January 22 - Collab 1 instead of Collab 2
• January 29 - Loew 310 (computer lab not available.)
• January 31* (Wednesday) - Collab 1 (3:30-4:00 only)
• February 5
• February 12
• February 19 - HOLIDAY
• February 21 (Wednesday)
• February 26
• March 5
• FINAL EXAMINATION WEEK - Scheduled final exam date is Thursday, March 15, 6:30-8:20 p.m. However, you can still plan to meet on Monday, March 12 if it doesn't conflict with other final exams the first year students will be taking.

Related Wiki Pages

• GettingStartedWithLaTeX
• SomeUsefulLaTeXTips
• HomeWorksAndLabs