MA Program Information
- Professional MA Statistics by Semester
STAT 201A: Introduction to Probability at an Advanced Level
Distributions in probability and statistics, central limit theorem, Poisson processes, modes of convergence, transformations involving random variables.
STAT 201B: Introduction to Statistics at an Advanced Level
Estimation, confidence intervals, hypothesis testing, linear models, large sample theory, categorical models, decision theory.
STAT 243: Introduction to Statistical Computing
Concepts in statistical programming and statistical computation, including programming principles, data and text manipulation, parallel processing, simulation, numerical linear algebra, and optimization.
Fall Semester Total Units: 12
STAT 222: Masters of Statistics Capstone Project
The capstone project is part of the masters degree program in statistics. Students engage in professionally-oriented group research under the supervision of a research advisor. The research synthesizes the statistical, computational, economic, and social issues involved in solving complex real-world problems.
STAT 230A: Linear Models
Theory of least squares estimation, interval estimation, and tests under the general linear fixed effects model with normally distributed errors. Large sample theory for non-normal linear models. Two and higher way layouts, residual analysis. Effects of departures from the underlying assumptions. Robust alternatives to least squares.
Spring Semester Total Units: 12
The program is for full-time students and is designed to be completed in two semesters (fall and spring). In order to obtain the M.A. in Statistics, admitted M.A. students must complete a minimum of 24 units of courses and pass a comprehensive examination.
In the first semester, all students will take intensive graduate courses in probability, theoretical statistics, and statistical computing; the typical courses are STAT 201A, 201B, and 243. In the second semester, students will take an advanced course in modern applied statistics (STAT 230), an elective, and a capstone course. The capstone will consist of a team-based learning experience that will give students the opportunity to work on a real-world problem and carry out a substantial data analysis project. It will culminate with a written report and an oral presentation of findings. The elective will depend on the student’s interests and will be decided in consultation with advisers. For a complete list of courses offered by the department and course descriptions, please visit the academic guide.
All coursework used for the M.A. must be letter graded unless the course is only offered on a satisfactory/unsatisfactory (S/U) basis. The total of S/U units may only be 2
Elective courses are chosen with the guidance and approval of the MA program Chair. Generally, the elective must be a graduate level course related to statistics. Such courses can be within the Statistics Department or from other departments. Some examples of past electives:
- STAT 260: Topics in Probability and Statistics
- COMPSCI 294: Special Topics in Computer Science (topics vary widely for special topics courses)
- COMPSCI 289A: Introduction to Machine Learning
- STAT 241A: Machine Learning
- IND ENG 263A: Applied Stochastic Process I
- Electives Approved for 2022/2023*
Dept Number Title Units COMPSCI 194-26 Intro to Computer Vision and Computational Photography 4 COMPSCI C281A Statistical Learning Theory 3 COMPSCI 271 Randomness and Computation 3 COMPSCI 289 Machine Learning 4 COMPSCI 282A Designing, Visualizing and Understanding Deep Neural Networks 4 CYPLAN 255 Urban Informatics and Visualization 3 EECS 227AT Optimization Models in Engineering 4 ELENG C227C Convex Optimization and Approximation 3 ESPM 215 Hierarchical Statistical Models in EnvSci 2 INDENG 235 Applied Data Science with Venture Applications 3 INDENG 262 Mathematical Programming (optimization) 4 INDENG 263 Applied Stochastic Processes 4 INDENG 265 Learning and Optimization 3 INDENG 242 Applications in Data Analysis 3 INFO 251 Applied Machine Learning 4 INFO 254 Data Mining and Analytics 3 INFO 256 Applied Natural Language Processing 3 INFO 259 Natural Language Processing 3 INFO C260F Machine Learning in Education 3 MATH 221 Advanced Matrix Computation 4 MBA 209F Fundamentals of Business 3 PBHLTH W214R Statistical Analysis of Categorical Data 4 PBHLTH 252D Causal Inference 1 4 STAT 150 Stochastic Processes 3 STAT 152 Sampling Surveys 4 STAT 153 Introduction to Time Series 4 STAT 154 Modern Statistical Prediction and Machine Learning 4 STAT 158 The Design and Analysis of Experiments 4 STAT 232 Experimental Design 4 STAT 248 Analysis of Time Series 4 STAT 260 Special Topics 3 STAT 215A/B Statistical Models: Theory and Application 4 STAT 256/156 Causal Inference 4
If an elective that you would like to take is not on the list the course can be submitted for department approval. You can submit your request using the Google Form here. If you take an approved elective that is less than 4 units you will need to take another elective and/or approved seminar course to meet the 24 unit minimum requirement for the program. *Approved electives are subject to change.
In extremely rare cases, a thesis option may be considered by the MA Chair. Typically, this will be when either the option has been offered to the student at the time of admission, or if the student arrives with substantial progress in research in an area of interest to our faculty. If approved by the MA Chair for the thesis option you will not have to take the comprehensive exam.
If approved for the thesis option, you must find three faculty to be on your thesis committee. Though not required, it is strongly encouraged that one of the faculty be from outside the Statistics Department. Both you and the thesis committee chair must agree on the topic of your thesis. Please provide a short description of your thesis topic, the names of your committee members and the signature of your committee chair on the Worksheet for the M.A. in Statistics, Thesis Option. In addition, you will also need to complete Graduate Division’s Application for Candidacy for the Master's Degree (Plan 1 - Thesis)
The MA program includes students who are admitted directly into the department and students obtaining advanced degrees in other departments at Berkeley. Coursework consists of intensive graduate courses in probability, theoretical statistics, and statistical computing as well as an advanced course in modern applied statistics and a capstone course. Students will have the option to take elective courses.
Will I be able to take courses other than those that are required?
Course selection will be done in consultation with Statistics Department MA Chair and/or committee member. Some students do take additional courses, including courses in other departments, depending on their background and level of preparation. Other professional graduate programs on campus all have their own policies for enrollment in their courses. After appropriate consultation, students will need to check these policies before registering for such courses.
Can I transfer to the PhD program?
There is no transfer arrangement into the PhD program. To gain acceptance into the PhD program, you must apply along with all other applicants, and you will be considered in the same way as other applicants. Students should know that admission to the UC Berkeley Statistics PhD program is highly competitive.
How to Advance to Candidacy
All coursework for the M.A. must be completed by the end of the semester in which you intend to graduate. In order to advancement to candidacy, you need to complete the MA comprehensive exam and completed all the required MA coursework. For those approved by the M.A. Program Committee Chair, to apply for the M.A. thesis option, you will have to submit individual application for advancement that list the proposed committee for the thesis, http://grad.berkeley.edu/wp-content/uploads/Mastcand.pdf.
If you already have a master's degree from any institution including UC Berkeley and are applying for advancement to candidacy for a master's degree in Statistics, you must:
- Provide a transcript (unofficial one)
Please submit your completed paperwork to the Master's Program Coordinator at 367 Evans Hall for review by the M.A. Program Committee. The department deadline to turn in paperwork is by the end of the third week of the semester in which you plan to graduate.
How do I add/drop classes or change my grading option between letter grading and satisfactory/unsatisfactory (SU)?
Each semester, graduate students have till the Friday of the third week of classes to add/drop courses on Cal Central. If you want to add/drop courses after the third week, you will have to complete a form called the Graduate Petition to Change Class Schedule. After completing the form, please submit it to the MA Program Coordinator in 375 Evans so that it can be processed. The form can be given in person or put in the MA Program Coordinator's mailbox in 367 Evans. It must be submitted before the last day of classes in each semester, which occurs before the week of final exams. See here for the academic calendar.
What is the proportion of international students for this program?
We do not admit students based on national origin and we do not have fixed proportions of domestic and international students. The city of Berkeley and the Department of Statistics have always had a diverse and lively international community.
For questions regarding visas, employment of international students, or any other questions regarding temporary stay in the United States, please visit the Berkeley International Office Website or call them at (510) 642-2818.