Statistics is the science--and art--of extracting data from the world around us and organizing, summarizing and analyzing it in order to draw conclusions or make predictions. This course provides a grounding in the principles and methods of statistics as commonly used in the natural and social sciences. Topics include: probability theory, data collection, description, visualization, probability, hypothesis testing, correlation, regression and analysis of variance. We will use the open source statistical computing package R (no prior computing experience is assumed).
Given that we have a small number of students with different backgrounds and goals, we're going to be a bit more flexible with the structure this semester. Each of you will design your own curriculum, including how you wish to be evaluated. There will be some constraints and, I hope, lots of group work as you either have some of the same goals or can usefully work on a project from different angles.
The usual main syllabus looks roughly like:
A couple of extra pieces I was planning to throw into the mix this semester:
You are expected to be aware of the college's policy on academic integrity and to abide by it. Please come and talk to me if anything is unclear.
If you think you qualify for accommodations under the ADA, contact Catherine O'Callaghan (firstname.lastname@example.org) to work out the details.
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