Applied Statistics Graduate Program
The Master of Science in Applied Statistics program trains students to utilize statistical methods to draw valid and meaningful inferences from data. Using a variety of statistical software (SAS, SPSS, Minitab, R), graduates are expected to analyze real-world data appropriately and communicate their findings effectively. The degree is granted to students who complete 30 units of course work and either pass two comprehensive examinations or fulfill the thesis/project requirement. Typically, the degree is obtained in four semesters.
More information can be found in M.S. in Applied Statistics - CSULB Catalog (23-24).
Upon completion of the program, students seek jobs as statistical analysts in industry, government, or academia. Some of the graduates continue on for a Ph.D. in other universities.
There are eight full-time faculty members who teach courses in this program. The course titles are:
- Introduction to Mathematical Statistics
- Data Analysis with SAS
- Random Processes
- Actuarial Science: Models
- Actuarial Science: Financial Mathematics
- Regression Analysis
- Statistical Inference
- Experimental Design
- Statistical Quality Control
- Survey Sampling
- Statistical Consulting
- Multivariate Statistical Analysis
- Nonparametric Statistics
- Statistical Simulation
- Computational Statistics
- Data Mining
- Data Informatics
- Time Series
- Survival Analysis
- Advanced Methods in Biostatistics
Graduate students have the following options:
- Comprehensive Exams
For the Thesis Option your abstract must be approved by the Statistics Committee.
Comprehensive Exams Option
For the Comprehensive Exams Option you must pass in two areas, Statistical Inference and Experimental Design. Both examinations must be taken in the same semester at your first trial. You are given two chances to pass both examinations.
The Project Option is only for full-time industrial employees, and the project topic and data must come from the work. You must show that the project would be beneficial to your company. You must get approval from the graduate advisor and an abstract must be approved by the Statistics Committee.
|Areas of Interest
|Dr. Yong Hee Kim-Park
|statistical inference, estimation, samply, actuarial statistics
|Dr. Sung Kim
|time series, computational statistics, experimental design
|Dr. Olga Korosteleva
|clinical trials, stochastic processes, actuarial statistics
|Dr. Seungjoon Lee
|statistical machine learning, data mining, multi-fidelity data fusion
|Dr. Hojin Moon
|biomedical statistics, decision-making algorithms, risk analysis
|Dr. Alan Safer
|data mining, multivariate statistics, time series
|Dr. Kagba Suaray
|survival analysis, density estimation, sampling
|Dr. Tianni Zhou
|clinical trials, survival analysis