The Department of Statistics at UC Riverside has an outstanding reputation in Teaching, Research and Consulting. We are the only program in Southern California where one may obtain a PhD in Applied Statistics. Our graduate programs offer opportunities to diversify your study to include research areas in a variety of academic disciplines such as:
Probability Theory • Experimental Design • Markov Chain Monte Carlo Methods • Longitudinal Data Analysis • Functional Data Analysis • Mixture Models • Machine Learning • Data Mining • Bioinformatics • High Dimensional Statistics and Inference • Multiple Testing
The Statistics faculty and staff are fully dedicated to graduate student success. As our graduate student, you will be able to work closely with faculty and other graduate students on innovative statistical research projects and be a part of department's successful Statistics Consulting Collaboratory that serves the campus and business community. Our faculty has received National/International recognition for their professional contribution in research, teaching and service.
Masters in Statistics
Fall 2022 MS application deadline extended to August 1! Contact firstname.lastname@example.org for more information.
The Master's Program has a professional orientation, emphasizing applications and applicable theory; it is intended to provide an "operational" knowledge of the subject.
To obtain the M.S. degree, students are required to complete 41 units and pass the comprehensive exams. Normative time to degree is 2 years.
To apply to the program, students must either have completed a B.S. degree in Statistics (or the equivalent), or have completed the following prerequisite courses: STAT 160A, 160B, 160C,161, 170A, 170B, and 171, covering basic areas of probability and statistics. These courses may be taken through concurrent enrollment via UCR's Extension Center or from another institutions that have these equivalent courses. View the description of these courses by clicking on: General Catalog
The undergraduate courses are not counted as credit towards the M.S. degree.
Changing degree objective from the M.S. to the Ph.D. is available for students that pass the comprehensive exams and are progressing well academically. Requests are submitted to the graduate advisor for approval, however, funding support is not guaranteed.
Ph.D. in Applied Statistics
The Ph.D. program in Applied Statistics emphasizes both the theory of Statistics and its application to special fields of interest. Primarily, students work on completing the course requirements and comprehensive exams during the first 2-3 years. A minimum of 12 units of enrollment (about 3 courses per quarter) is required until advancing to candidacy. Students begin dissertation research after successfully passing the course requirements and comprehensive exams. Part of the course requirements is the opportunity to take courses outside the department that will allow students to prepare for their research project. This is the "Substantive Field" requirement and courses may be chosen from areas in Biology, Economics, Political Science, Psychology or Administration. Specialties might include Population Genetics, Biological Control, Hydrology, Epidemiology, Geology, Discrimination of Learning, or scales and Measurements. Other subjects will need prior approval from the graduate advisor.
To apply to the Ph.D. program, students must have completed either a Bachelor's Degree or a Master's Degree in Statistics, Computer Science, Mathematics, or some other quantitative based discipline. Students lacking sufficient preparation for some statistics graduate classes must complete some preparatory work in Statistics, Computer Science, or Mathematics depending on their background.
View a list of requirements and specific courses to Advance to Candidacy for Ph.D. degree by clicking on: General Catalog
Master of Science in Business Analytics (MSBA)
Fall 2022 Application Deadlines:
- Priority Round: December 15
- Round 2: January 31
- Round 3: March 31
- International Late Round: June 1
- Domestic Late Round: August 1
Build a career in the growing and important field of business analytics. As firms have access to increasingly large amounts of data about their customers, costs, and suppliers, highly trained analysts who examine this information have become essential for improving operations, increasing the yield on marketing programs, and optimizing pricing and financing. UCR’s graduate degree in business analytics will extend your background in business or a quantitative discipline to bring your business acumen and statistical computing skills to a level that allows you to make the most of this vast business data.
The UCR graduate program in Business Analytics is a rigorous STEM program jointly offered by the School of Business and the Department of Statistics in the College of Agricultural and Natural Sciences.
The curriculum focuses on:
- Statistical computing to describe marketing, logistics and financing patterns
- Testing models for improved operating efficiency, lowering costs and targeting the needs of customers
- Forecasting revenues and consumer demand
- Identifying trends in financial markets and using financial data to hedge operations
All students in the program take highly quantitative courses in data analysis and statistical computing, as well as a two-quarter, experiential learning capstone class that applies your understanding of business analytics to a project.
Gain your degree in nine months of intensive study or follow a flexible schedule that combines your studies with industry work experience.
Three Career Tracks through Elective Courses:
- Finance Analytics: Explore this new and growing specialization within business analytics by focusing on investments and portfolio management, and derivatives.
- Marketing Analytics: Use data on demographics, consumer behavior, markets, and social media to leverage information for more powerful marketing strategy. Marketing analytics careers can be found in consulting as well as large companies with a national or international footprint.
- Operations Analytics: Supply chain and logistics management requires informed decision-making based on hard numbers that pinpoint bottlenecks and optimize growth. Operations analytics training prepares you to extract insights in manufacturing, distribution, and app-based services.