Outline. Statistics 202a: Statistical Programming, Prof. Rick Paik Schoenberg.

FALL 2011.

Lectures: Tues/Thur 11am-12:20pm in Geology 3656.

Texts:
1) R Cookbook, by Paul Teetor.
The text is on reserve in the SEL-EMS library.
2) Absolute C, by Walter Savitch.

Office hours: Thursdays, 12:30pm to 1:30pm, MS 8965.

email: frederic@stat.ucla.edu

Course Website: http://www.stat.ucla.edu/~frederic/202a/F11 Statistics 202a will explore computational statistics and will focus especially on computing in R and C/C++.

The course is designed for graduate students in any discipline with solid mathematical backgrounds and some knowledge of basic statistics.

A preliminary outline of the class is given below.

1. R basics (ch. 1-3 of Teetor).
2. Managing input and Output in R, functions and data structures in R (ch. 4-5).
3. Data transformations, strings, and dates in R (ch. 6-7).
4. Generating random variables, combinations and permutations, and basic statistical summaries in R (ch. 8-9).
5. Graphics in R (ch. 10).
6. Regression and ANOVA in R (ch. 11).
7. Optimization, PCA, and basic time series analysis in R (ch. 12-14).
8. C basics.
9. Functions and loops in C.
10. Using C in R.
11. Variables, arrays, structures, strings, and pointers.
12. Input and output in C.

Grading:
Homeworks (50%), written project (35%), oral presentation/participation (15%).

Attendance in class is generally not mandatory and not counted as part of the grade. There will be no extensions for the project or presentation. Students who are unable to make these dates or otherwise fulfill the course requirements must consult with the instructor in advance, if possible. Students with learning disabilities must consult with the instructor by the 2nd week of class if special arrangements are required.

Written Project: due Thur, Dec 8, 11:59pm, by email to frederic@stat.ucla.edu.
Oral presentations: Nov 29-Dec 1.

No class Thur, Nov 24 (Thanksgiving).
No final exam.

Description of Written Project:
(to come)

Oral presentations of project results will take place on the last 2 class periods. These will involve simply presenting a clear, concise, and very brief summary of your data and a couple of the main results from your analysis.