Professor: Robert Gould
Office: MS 6151
Hours: Wednesdays at 2pm & Fridays at 10am.
Phone: 20(6-3381)
email: rgould@stat.ucla.edu or rgould@ucla.edu
Getting Started:
1) Buy the book.
You have a choice, depending on your discipline:
Multivariate Geostatistics, Hans Wackernagel, Springer Verlag2) Download the software
Astrostatistics, G.J. Babu and E.D. Feigelson, Chapman & Hall
Statistical Methods in the Atmospheric Sciences, Daniel S. Wilks, Academic Press
About the Computer:
We'll be meeting once a week (during class) in the Statistics computer lab on the 9th floor of Boelter Hall. The computers are Macs (iMacs, actually) which I know causes untold consternation in some quarters. Do not worry; you are allowed to use any computer you want or have access to. The purpose of meeting in the lab is merely to demonstrate some statistical techniques, which you can then take with you. However, you will need regularly access to a computer in order to complete the homework and exams. So please see me immediately if you do not have access to a computer.
About the Software:
ViSta is a "front end" to the statistical programming language xlispstat.
It runs on Windows, Mac, and Unix systems. ViSta is designed to analyze
multi-variate data, and comes with much excess baggage. Also, if
you do not have multi-variate data, then it is a little like swatting a
fly with a bomb. We will therefore use xlispstat fairly frequently
for more "simple" data sets. The ViSta user's manual is a good introduction
to that tool, and the "Surfer's Guide" gives you some idea of how to get
started using xlisp-stat. You are welcome to use any statistical
package you are comfortable with; ViSta is recommended only because it
is free and has good tools built-in. The purpose of the course is
to teach data analysis, not a software package. So don't get caught
up in the details of how to use the software.
Grading
Grades will be based on
Midterm
during Week 6 (20%) (See the midterm: requires adobe acrobat
reader.)
Project (40%)
Final (40%)
Undergraduates enrolled can get credit for their homework (10%) and
the final is then worth 30%.
Grades will be maintained on my.gradebook,
which I understand is accessible via my.ucla.edu.
Homework
A list
of homework problems.
Handouts
Basic Bootstrapping: notes from class.
Basic
Bootstrapping lisp function. Cut and paste it into the
listener window to do very basic, somewhat clumsy, bootstrapping.
First
xlisp-session. From lecture notes. Requires Adobe Acrobat Reader.
Comparing
estimators. From lecture notes. Discussion about median
vs. mean with simulation results.
Data Sets
Most of the data
sets used in this class are accessible bia this link. This directory
contains multiple versions of the data. This almost always includes the
raw version, as well as a lisp version, and sometimes a Stata version.
Events
of Interest
I'll try hard to list "extra-curricular" activities that might be of
interest to students in this class (and others).