Department of Statistics, Middle East
Technical University
CORRESPONDENCE ANALYSIS & RELATED METHODS
Universitat Pompeu
Fabra, Barcelona
Slides
Week 1 (colour, for
viewing) Week
1 (black&white, for printing) Video: data
in 3-d and rotation to best-fitting plane Video:
multiple regression and contour lines
Week 2 (colour, for
viewing) Week
2 (black&white, for printing)
Week 3 (colour, for
viewing) Week
3 (black&white, for printing)
Week 4 (colour, for
viewing) Week
4 (black&white, for printing)
Week 5 (colour, for
viewing) Week
5 (black&white, for printing)
Week 6 (colour, for
viewing) Week
6 (black&white, for printing)
Week 7 (colour, for
viewing) Week
7 (black&white, for printing)
Week 8 (colour, for
viewing) Week
8 (black&white, for printing)
Homeworks
Homework week 1:
During Bayram holiday: read and study Chapters 1-3 of Biplots in Practice
downloadable from http://www.multivariatestatistics.org
Homework week 2
Fill in this data form rating the dissimilarities
between countries and then do homework described here.
Homework week 3:
Fill in this new data form rating the attributes of
each country and then do the homework described here. Read Chapter 4 of Biplots
in Practice.
Homework week 4:
The homework is described here. Also read Chapter 5
and Chapter 6 of Biplots
in Practice. Look seriously for
data for your projects!
Homework week 5:
Read Chapter 8 of Biplots in Practice, downloadable from http://www.multivariatestatistics.org. Soon you should have your actual data, we
will start scheduling extra classes now for work on your projects.
Homework week 6:
Read Chapter 23 of Correspondence Analysis in Practice, which you can download here.
Homework week 7:
Read Chapters 9 and 10 of Biplots in Practice, downloadable
from http://www.multivariatestatistics.org.
Extra reading for
week 8: Read Chapter 7 of Biplots in Practice, downloadable
from http://www.multivariatestatistics.org.
R
scripts
Data
sets
The data sets
used in class can generally be obtained from http://www.multivariatestatistics.org.
Support
reading material (some of these links are not active yet...)
Kuhnert & Venables Introduction to R
Thomas Lumley’s fundamentals of R programming
Using
R for data analysis and graphics by
Maindonald .RData
workspace, file ‘usingR.RData’ accompanying this article
Appendix A (Theory of Correspondence
Analysis) of Correspondence Analysis in Practice
Full
text of La Práctica del Anàlisis de Correspondencias by Michael
Greenacre
Journal of Statistical
Software article on ca package by Nenadic & Greenacre (2007)
Additional
reading (some
of these links are not active yet...)
Almost final
version of my paper Contribution
Biplots (to be published in Journal of Computational & Graphical
Statistics).
Popular
article on correspondence analysis
Publishing
quantitative results
Dynamic
perceptual mapping Dynamic
graphics videos
Encyclopedia
of Political Science
CARME
network
CARME network videos
Statistical songs
www.youtube.com/StatisticalSongs
Basic information
Class time: Wednesday mornings
9:40-12:30
Classroom:
Department of Statistics building, ground floor, room Z22
Homework and class
attendance & participation counts 20% towards final grade.
Final project and
project presentation counts 80% towards final grade.
My office hours for
seeing students: Wednesday afternoons, 14:00-16:00.
You can also arrange
a meeting at other times by speaking me at the class or contacting me by email.
Please use the
following email address for communication about this course:
mmr.upf [at] gmail.com