STAT 133

Stat 133: Concepts in Computing with Data

Sample Exam Questions

Instructor
- Deborah Nolan
  - Office: 395 Evans
  - Email: nolan@stat.berkeley.edu
  - Office Hours: Mon 1:00-2:00 and Wed 11:00-12:00
GSI
- Charlotte Wickham
  - Office: 342 Evans
  - Email: wickham@stat.berkeley.edu
  - Office Hours: Wed 3-4pm, Thu 11-1pm, Fri 1-2pm
Student Assistants
- Jeremy Shen and Kheng Chew
  - Office: 342 Evans
  - Email:
  - Office Hours: TBA

Class meets MWF: 2-3 in 150 GSPP

Lab meets on Fridays: 3-4 or 4-5 in 342 Evans

Syllabus for the course

Course Resources

There is NO textbook for the class. Chapters of a draft manuscript will be made available on bspace throughout the semester.
We will use R as the primary computational environment
R manuals
- Using R for Data Analysis and Graphics - Introduction, Examples and Commentary by John Maindonald
- R for Beginners by Emmanuel Paradis
- An Introduction to R
- R Data Import/Export
- R Language Definition

Computing Resources: Statistical Computing Facilities (SCF) - networked computers running Unix
Undergraduate computer laboratory
- 342 Evans (25 iMacs) and 432 Evans (12 SUNs)
- Open 8am to 6pm Monday through Friday.
- Remote access through ssh and Exceed. Nathan Chan has instructions on how to install Exceed.
Discussion Board, Announcements, and Chat Room: bspace.Berkeley.edu

Grading

Participation	4%	Discussion board, chat room, and class discussion
Homeworks	24%	8 Short computing assignments each worth 3%
Projects	60%	4 each worth 15%
		Must be done in groups of 2 or 3
		Possible topics: Geolocation, Adhoc network simulation, GUI development
Final	12%	Written final exam Saturday, Dec 16 5-8pm

Expectations: Although there is no computing, probability, or statistics prerequisite for this course, there is an expectation that you have the Curiosity, Initiative, and Motivation to Explore on your own and Learn as needed.

2006-08-28