Department of Statistics and Biostatistics

The Department Office is part of the Quantitative and Behavioral Science HUB and is located on the 2nd Floor of the North Science (SC-N) building, Room 229.

Open 9:00 a.m. - 6:00 p.m., Monday -  Fridays.

Dept. Phone: (510) 885-3435

Faculty

Professors

Ayona Chatterjee (Chair), Ph.D. University of Edinburgh (United Kingdom)

Shenghua (Kelly) Fan, Ph.D. University of Minnesota

Joshua D. Kerr, Ph.D. University of California, Davis

Eric A. Suess, Ph.D. University of California, Davis

Mitchell R. Watnik, Ph.D. University of California, Davis

YanYan Zhou, Ph.D. University of Maryland

Associate Professor

Eric Fox, Ph.D. University of California, Los Angeles

Li Zou, Ph.D. State University of New York

Assistant Professors

Tae Joon Kim, Ph.D. Kansas State University

Jiyoun Myung, Ph.D. University of Florida

Wendy Rummerfield, Ph.D. University of California, Irvine

Statistics Graduate Coordinator: Prof Joshua Kerr.

Biostatistics Graduate Coordinator: Prof Kelly Fan.

Department Statement

A degree in Statistics, Data Science and Biostatistics presents many job opportunities and has diverse areas of applications such as Data Analysis, Health Informatics, Biostatistics, Finance, Government, Actuarial
Science, Bioinformatics, Medical Statistics, Pharmaceutical, Biotech, Banking, Education, Consulting, and many others. Students are encouraged to consider the fields of Statistics and Data Science as a program of study,
whether graduate or undergraduate. Many of the Department’s undergraduate students are double-majors. Computer Science, Math, and Psychology majors, in particular, have found double-majoring with Statistics
to be valuable in getting a job or pursuing higher degrees. Pursuing a minor in Statistics, Data Science or Biostatistics can greatly enhance the value of any degree in today’s data-intensive world.

About the Department

Use our university website link to learn more about what the Statistics and Biostatistics Department has to offer.

• Scholarships
• Actuarial Science
• Advising
• Biostatistics (PSM)
• Statistics Organizations
• Resources
• And more…

Programs

• Statistics, B.S.
• Statistics, B.S.: Data Science Concentration

• Biostatistics Minor
• Data Science Minor (18 units)
• Statistics Minor

• Biostatistics, M.S.
• Statistics, M.S.
• Statistics, M.S.: Actuarial Science Concentration
• Statistics, M.S.: Applied Statistics Concentration
• Statistics, M.S.: Data Science Concentration
• Statistics, M.S.: Mathematical Statistics Concentration

• Applied Statistics Certificate
• Theoretical Statistics Certificate

Courses

• BSTA 661 - Categorical Data Analysis
• BSTA 662 - Survival Analysis
• BSTA 663 - Clinical Trials in the Pharmaceutical and Biomedical Industries
• BSTA 665 - Survival Data Analysis using SAS
• BSTA 668 - Longitudinal Data Analysis
• BSTA 697 - Issues in Biostatistics

• DATA 105 - Math for Data Science 1
• DATA 130 - Data Science Profession
• DATA 205 - Math for Data Science 2
• DATA 312 - Data Analysis with Python
• DATA 340 - Data Science Ethics
• DATA 492 - Capstone Project

• STAT 100 - Elements of Statistics and Probability
• STAT 100A - Statistics Principles
• STAT 101 - Statistics in Everyday Life
• STAT 101A - Everyday Statistics Principles
• STAT 110 - Elements of Statistics for Business and Economics
• STAT 130 - Data Science Profession
• STAT 206 - Public Health Informatics and Technology
• STAT 215 - Introduction to Data Science
• STAT 303 - Statistical Methods in Biology
• STAT 303A - Biostatistics for Health Science
• STAT 306 - Public Health Informatics: The Role of Data
• STAT 310 - Statistical Methods in the Social Sciences
• STAT 312 - Data Analysis with Python
• STAT 316 - Statistics and Probability for Science and Engineering
• STAT 320 - Introduction to Probability Theory I
• STAT 321 - Probability Through Simulation
• STAT 330 - Statistical Inference
• STAT 331 - Introduction to Analysis of Variance
• STAT 340 - Data Science Ethics
• STAT 351 - Sampling Procedures for Surveys
• STAT 398 - Internship
• STAT 406 - Emerging Technologies for Public Health
• STAT 416 - Public Health Maps and Spatial Analysis for Health Equity
• STAT 432 - Introduction to Linear Regression and Logistic Regression
• STAT 450 - Introduction to R for Data Science
• STAT 451 - Introduction to Data Visualization
• STAT 452 - Introduction to Statistical Learning
• STAT 473 - Introduction to Nonparametric Statistics
• STAT 474 - Introduction to Time Series and Forecasting
• STAT 475 - Introduction to Stochastic Processes
• STAT 481 - Bayesian Statistics
• STAT 490 - Independent Study
• STAT 492 - Capstone Project
• STAT 495 - Data Analysis with SAS
• STAT 497 - Issues in Statistics
• STAT 498 - Internship

• STAT 620 - Probability and Statistical Theory
• STAT 630 - Statistical Methods
• STAT 631 - Analysis of Variance Models
• STAT 632 - Linear and Logistic Regression
• STAT 640 - Advanced Statistical Theory
• STAT 641 - Bootstrapping Methods
• STAT 650 - Advanced R for Data Science
• STAT 651 - Data Visualization
• STAT 652 - Statistical Learning
• STAT 653 - Statistical Natural Language Processing
• STAT 654 - Introduction to Applied Deep Learning
• STAT 660 - Advanced SAS I
• STAT 661 - Categorical Data Analysis
• STAT 671 - Advanced JMP
• STAT 673 - Nonparametric Statistical Methods
• STAT 674 - Time Series
• STAT 675 - Advanced Stochastic Processes and Simulation
• STAT 676 - Advanced Probability
• STAT 690 - Independent Study
• STAT 692 - Comprehensive Exam Review
• STAT 694 - Applied Research in Statistics and Biostatistics
• STAT 697 - Issues in Statistics
• STAT 698 - Internship