Statistical Programming, Prof. Rick Paik Schoenberg.
Lectures: Tues/Thur 11am-12:15pm in Lakretz 120.
1) R Cookbook, by Paul Teetor (2011).
The text is on reserve in the SEL-EMS library, and
available for free to UCLA students on Safari Books Online
via UCLA LearnIt (http://www.learnit.ucla.edu)
and can be accessed on campus or off campus using a VPN
2) The C programming language, 2nd edition,
by BW Kernighan and DM Ritchie (1988).
Office hours: Tuesdays, 10-10:50am, MS 8983.
Course Website: http://www.stat.ucla.edu/~frederic/202a/F13 .
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. Managing input and output in C.
Homeworks (85%), written group project (10%),
oral presentation/participation (5%).
Attendance in class is generally not mandatory and not
counted as part of the grade.
Late homeworks will not be accepted at all.
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 Sun, Dec 8, 11:59pm, by email to email@example.com.
Oral presentations: Nov 21-Dec 5.
No class Thur, Nov 28 (Thanksgiving).
No final exam.
Description of Written Project:
Oral presentations of project results will take place in class on Nov 21 - Dec 5.
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.
More description will be given in later lectures.