Stats 201A: Research Design, Sampling and Analysis
Syllabus
(Fall
2024)
BruinLearn homepage: https://bruinlearn.ucla.edu/
Web Resources: http://www.stat.ucla.edu/~hqxu/stat201A/
Time/Place: TR 2-3:15pm /
Boelter Hall 5440
; Discussion: W 11-11:50am/ Boelter Hall 5422
Instructor:
Hongquan Xu
<hqxu@stat.ucla.edu>; TA:
Danny Ying
Office Hour: T 3:30-4:30pm in MS 8955, F
2:30-3:30pm via Zoom, and by appointment.
Textbooks (1-2)/References
(3-6):
- C. F. J. Wu and M. S. Hamada
(2021). Experiments: Planning,
Analysis and Optimization, 3rd ed., Wiley.
Library has E-book.
- S. K. Thompson (2012). “Sampling," 3rd ed., Wiley.
Library has E-book.
-
D. C. Montgomery (2005-2020). 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, 14) 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
Thursday, December 12
(3-6pm).
- Final group project report (30%)
due Saturday, December 14.
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.