I am a professor in the CSULB department of Mathematics and Statistics, and currently serve as graduate advisor for the Applied Statistics M.S. program.
Doctor of Philosophy in Mathematics
University of California, San Diego
Bachelor of Science in Mathematics
California State University, Long Beach
"The function of education is to teach one to think intensively and to think critically. Intelligence plus character: that is the goal of true education."
-Rev. Dr. Martin Luther King, Jr.
I am not teaching this semester, but you can find resources from previous semesters here
STAT 108: Statistics for Everyday Life
MATH 113: Precalculus Algebra
MATH 123: Calculus II
MATH 224: Calculus III
MATH 247: Linear Algebra
STAT 380: Probability and Statistics
STAT 381: Mathematical Statistics
STAT 482: Random Processes
STAT 483: Survey Sampling
STAT 510: Regression Analysis
STAT 520: Statistical Inference
STAT 560: Nonparametric Statistics
STAT 697: Extreme Value Theory
My research interests include nonparametric functional estimation, extreme value theory, sports analytics, and using data to improve pedagogy. Please find some of my publications linked below.
- Bootstrap bandwidth selection for a smooth survival function estimator from censored data. with Berg, A. Journal of Statistical Research 44, no. 2 (2010): 207-217.
- On the asymptotic distribution of an alternative measure of kurtosis. International Journal of Advanced Statistics and Probability 3, no. 2 (2015): 161-168
- Student performance and attitudes in a collaborative and flipped linear algebra course. With Jen-Mei Chang and Julia Murphy. International Journal of Mathematical Education in Science and Technology. 47, no. 5 (2016): 653–673.
Established in 2003, the Master of Science in Applied Statistics program at CSU Long Beach is an academic degree program which trains students to draw valid inferences from data. Using conceptual foundations and statistical software packages (SAS, R, and Python), graduates are expected to analyze real world data appropriately and communicate their findings effectively. The tools you learn here will open the door for careers in data science and analytics, or prepare you for a PhD. Typically, the requirements can be satisfied in about 4 semesters. As one of the largest statistics programs at masters granting institutions in the United States, we are building a nationwide network of alumni in industry and academia.
If you are interested in applying to the program, download the FAQ sheet, and contact me if you have any further questions. There are two simple steps to applying. First, initiate the process at Cal-State Apply. Next fill out the prerequisite worksheet, and email it to me. We welcome domestic and international students.
As students in our program, you are an instrumental part of it's success. Your passion for data analysis and hard work help foster a collaborative learning environment, with faculty support. The links below will help you navigate the process from matriculation to graduation.
We are proud of the achievements of our alumni.
You can contact me through email, and find me on social media. I’ll get back to you as soon as I can.
As graduate advisor for the Applied Statistics M.S. program, I'm here to help you get one step closer to your degree. Please use the button below to request an appointment.
FALL 2022 Advising hours via Zoom/Teams video conferencing are
M 5-7PM by appt. only.
Get in touch with students studying Applied Statistics at CSULB, and check out the exciting opportunities publicized by the Statistics Student Association!
Sung Kim, PhD--Time Series, Computational Statistics, Multivariate Analysis, SAS
Olga Korosteleva, PhD--Survival Analysis, Survey Sampling, Statistical Consulting, Actuarial Statistics, SAS
Xiyue Liao, PhD--Regression Analysis, Multivariate Analysis, Data Science with R, Statistical Machine Learning, Actuarial Statistics, SAS
Hojin Moon, PhD--Regression Analysis, Nonparametric Statistics, Statistical Inference, Special Topics in R
Alan Safer, PhD--Data Mining, Data Informatics
An Introduction to Statistical Learning by James, Witten, Hastie and Tibshirani is an excellent textbook emphasizing the application of many of the modern statistical techniques used in data science. Their website is full of resources, including R code, and video tutorials.
Online computing: Virtual Lab @CSULB
A Graphical User Interface (GUI) for Data Mining in R: RATTLE
Mathematicians of the African Diaspora is an encyclopedic website provided by the SUNY Buffalo.
Data visualizations by W.E.B DuBois, first black Harvard PhD, scholar, and founding father of American sociology.
The Hesabu Circle: A mathematical space for connection for the entire Black community, from pre-K to post-Doc.
Sloan Sports Analytics Conference --This conference at MIT is the engine that has driven the sports analytics movement, in a lot of ways. If you navigate to the “Past Conferences” and select “Annual Recaps”, there are tons of articles and videos, where you can see the use of statistical techniques in just about all sports contexts.
Journal of Quantitative Analysis in Sports--a wealth of scholarly articles on sports statistics. We have some access when logged in to the CSULB library website, OR when logged in to Beachnet if you happen to be on campus.
Miscellaneous Resources --compiled by CSULB students.