Neuroscience 9506
Instructor: Dr. Paul Gribble
BYOL (bring your own laptop) and please install R
Class Schedule 2010
1. Fri. Jan 15, 9:30-12noon *** RRI 5260a ***
2. Fri. Jan 22, 9:30-12noon RRI 4th floor conference room
3. Fri. Jan 29, 9:30-12noon RRI 4th floor conference room
4. Fri. Feb 5, 9:30-12noon RRI 4th floor conference room
5. Fri. Feb 12, 9:30-12noon RRI 4th floor conference room
xxx Fri. Feb 19 NO CLASS xxx
6. Fri Feb 26, 9:30-12noon RRI 4th floor conference room
7. Fri Mar 5, 9:30-12noon RRI 4th floor conference room
8. Fri. Mar 12, 9:30-12noon RRI 4th floor conference room
xxx Fri. Mar 19 NO CLASS xxx
9. Fri. Mar 26, 9:30-12noon RRI 4th floor conference room
xxx Fri. Apr 2 NO CLASS xxx
10. Fri. Apr 9, 9:30-12noon RRI 4th floor conference room
Course notes & readings: click [ here ]
(password protected, ask me for the password)
Course Description: The goal of the seminar is to provide students with the opportunity to gain a deeper understanding of the logic behind inferential statistics, and to learn a common base of standard multivariate statistical techniques. The course is not particularly oriented towards the arithmetic calculations underlying statistical procedures, rather we will focus on gaining an understanding of the logic behind various parametric and non-parametric statistical techniques common in the neurosciences. There will be a practical aspect to the course, namely learning to use R for statistical computation and graphical display of data.
The course is different than Computational Neuroscience I: Data Analysis, which is focused on using Matlab for data processing and analysis.
My plan is to divide up each session into a theoretical component, and following a short break, a practical component in which we review how to use R to conduct various statistical analyses and generate graphical representations of data. If you have taken the course in prior years (in which we used SPSS instead of R) and you are interested in learning about R, please get in touch with me, you are welcome to sit in on the practical sessions.
Mandatory textbook: (available at the UWO bookstore)
Designing Experiments and Analysing Data: A Model Comparison Perspective (2nd Edition) by Scott E. Maxwell & Harold D. Delaney. Lawrence Erlbaum Associates (2003). ISBN: 0805837183. Cost is $113.95 at the UWO bookstore, $82.59 at Amazon.ca, and $75.14 (USD) at Amazon.com. This book is mandatory.
Recommended textbooks: (available at the UWO bookstore)
Design and Analysis: A Researcher’s Handbook (4th Ed.) by Geoffrey Keppel. Prentice Hall (2004). ISBN: 0135159415. Cost is $171.90 at the UWO bookstore, $159.50 at Amazon.ca, and $118.92 (USD) at Amazon.com. This is a very good book showing computational examples of all sorts of ANOVA and regression situations. You should get this book.
Introductory Statistics with R by Peter Dalgaard. Springer-Verlag (2002 ). ISBN: 0387954759. Cost is $68.95 at the UWO bookstore, $60.25 at Amazon.ca, and $48.11 (USD) at Amazon.com. Reasonable (but not 100% appropriate for our purposes) intro book on using R to do various statistical procedures.
Statistics: An Introduction using R by Michael J. Crawley. John Wiley & Sons (2005). ISBN: 0470022981. Cost is $59.99 at the UWO bookstore, $47.99 at Amazon.ca, and $38.84 (USD) at Amazon.com. Again, a reasonable (but not 100% appropriate for our purposes) intro book on using R to do various statistical procedures.
Evaluation:
- 90% weekly assignments
- 10% participation
Please contact Carol Anderson (canders3@uwo.ca) if you are interested in registering for this course.
page last updated: Jan 5, 2010 14:02
