Stats 201A: Research Design, Sampling and Analysis
Syllabus
(Fall
2022)
BruinLearn homepage: https://bruinlearn.ucla.edu/courses/143502
Web Resources: http://www.stat.ucla.edu/~hqxu/stat201A/
Time/Place: TR 9:30-10:45am/
Kaplan Hall
Room 135; Discussion: M 11-11:50am/Public
Affairs Building 2250
Instructor:
Hongquan Xu
<hqxu@stat.ucla.edu>; TA:
Samuel
Onyambu <onyambu@g.ucla.edu>
Office Hour: W 3-4pm via Zoom; R 3-4pm via Zoom or in MS 8955
(Subject to change).
Textbooks (1-2)/References
(3-6):
- C. F. J. Wu and M. S. Hamada
(2009). Experiments: Planning, Analysis and Optimization,
2nd ed., Wiley. First edition is fine.
- S. K. Thompson (2012). “Sampling,"
3rd ed., Wiley.
-
D. C. Montgomery (2005-2019). Design and Analysis of Experiments,
6-10th ed., Wiley.
-
T. Lumley (2010). "Complex
Surveys: A Guide to Analysis Using R", Wiley.
- S. Sheather (2009) "A
Modern Approach to Regression with R",
Springer. Library has E-book.
- J. J. Faraway (2005/2014). "Linear Models
with R," Chapman & Hall.
Overview: We will
spend 6-7 weeks on experimental design and 3-4 weeks on sampling.
Tentative topics include
- Research Design: Basic
principle, ANOVA, blocked designs, factorial designs,
fractional factorial designs, response surface methods, computer
experiments and space-filling designs. [Wu and Hamada (Ch. 1-5,
8, 10) and notes]
- Sampling: Unequal
Probability Sampling, Regression Estimation, Stratified
Sampling, Cluster and Systematic Sampling, Multistage
designs. [Thompson (Ch. 1-6, 8, 11-13)]
Grading Policy:
- Participation (10%: Evaluation of peer presentations)
- Homework (30%) No Late
Homework.
- Group project presentation (30%: peer
evaluation) Week 10 or
Tuesday, December 6
(3-6pm).
- Final group project report (30%)
due Saturday, December 10.
Group Project:
You are encouraged to work with other 1-2 students. The whole
group hand in one written report.
(a) Design an experiment, collect data and perform analysis,
(b) Find 3 published experiments/data, redo the analysis (with
improved results), (c) Other ideas (get approval first).
Statistical Software:
You are expected to be familiar with one statistical software (e.g.,
R, S+, SAS, Stata, etc.). You are expected to know how to
perform linear regression and make various plots. R is a
language and environment for statistical computing and
graphics. You can download R and get information from the R
Home Page (http://www.r-project.org/).
Academic Integrity: As a student and member of the University
community, you are here to get an education and are, therefore,
expected to demonstrate integrity in your academic endeavors. All
students must uphold University of California Standards of Student
Conduct as administered by the Office of the Dean of Students.
Students are subject to disciplinary action for several types of
misconduct, including but not limited to: cheating, multiple
submissions, plagiarism, prohibited collaboration, facilitating
academic dishonesty, or knowingly furnishing false information. You
may have assignments or projects in which you work with a partner or
with a group. For example, you are welcome, and even encouraged, to
work with others to solve homework problems. Even though
you are working together, the assignment you submit for a grade must
be IN YOUR OWN WORDS, unless you receive specific instructions to
the contrary. For more information about academic integrity,
please go to http://www.deanofstudents.ucla.edu.
COVID-19
Policy: Please see the latest information/policy at covid-19.ucla.edu.