syllabus
info
title Statistics
term Spring 2016
credits 4
time Tue/Thu 8:30am - 9:50am
place Sci 217
level intro
faculty Jim Mahoney (covering for Matt Ollis, on sabbatical)
repeat not for credit
prereq none
blurb
Statistics is the science---and art---of extracting data from the world around us and organising, summarising and analysing it in order to draw conclusions or make predictions. This course provides a grounding in the principles and methods of statistics. Topics include: probability theory; collecting, describing and presenting data; hypothesis testing; correlation and regression; and analysis of variance. Two themes running through the course are the use of statistics in the natural and social sciences and the use (and abuse) of statistics in the news media. We will use the open source statistical computing package R (no prior computing experience is assumed).
textbook & software
work & grades
Your term grade will be weighted as follows.
- 15% three or so in-class tests
- 20% final project presentation and paper, either examining the use of statistics in some aspect of public life or looking at a specific use of statistics in your principal academic field
- 30% four or so homework assignments (about every two weeks)
- 35% final exam, 24-hour open-book take-home
Your grade may be adjusted up or down based on attendance, participation, preparation
for class, promptness of assignment submission, and engagement with the material. Unless
your case is exceptional, this adjustment will be by at most one letter grade.
academic integrity
The short version is that you must be explicit about what is your work
and what isn't - quoting sources and giving credit to others.
Please talk to me if you have any questions about any of this.
