Master of Arts in Statistics Program Information
- Professional MA Statistics by Semester
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Fall 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.
Units: 4
STAT 201B: Introduction to Statistics at an Advanced Level
Estimation, confidence intervals, hypothesis testing, linear models, large sample theory, categorical models, decision theory.
Units: 4
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. Python, SQL, and other tools are used in this course.
Units: 4
Fall Semester Total Units: 12
Spring Semester
STAT 214: Data Analysis and Machine Learning for Real-World Decision Making
Students will be engaged in open-ended data projects for decision making to solve domain problems. It mirrors the entire data science life cycle in practice, including problem formulation, data cleaning, exploratory data analysis, statistical and machine learning modeling and computational techniques, and interpretation of results in context.
Units:4
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.
Units 4
Approved Elective
Units 4
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 MA in Statistics, admitted MA 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.
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 popular past electives:
- STAT 248: Analysis of Time Series
- STAT 254: Modern Statistical Prediction and Machine Learning
- STAT 260: Topics in Probability and Statistics
- Electives Approved for 2024/2025*
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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 PBHLTH W214R Statistical Analysis of Categorical Data 4 PBHLTH C240C Biostatistical Methods: Computational Statistics 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 C241B Advanced Topics in Learning and Decision Making 4 STAT 248 Analysis of Time Series 4 STAT 254 Modern Statistical Prediction and Machine Learning 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 M.A. 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 M.A. 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 MA 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)
Professional Development
Prepare for a career in data science and statistics with our Professional Development resources. Workshops, alumni insights, and individual advising sessions are available to help you succeed.
Summer Prep Program
Equip yourself for your MA Statistics journey with our intensive 2-week Summer Prep Program. Strengthen your mathematical foundations, explore statistical concepts, and dive into probability theory.
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 process into the PhD program. To be accepted, you must apply and be evaluated alongside all other applicants during the current admission cycle. Please note that admission to the UC Berkeley Statistics PhD program is highly competitive.
How to Advance to Candidacy
All coursework for the MA must be completed by the end of the semester in which you intend to graduate. In order to advance to candidacy, you need to complete the MA Statistics Comprehensive Exam and complete all the required MA coursework. For those approved by the MA Program Committee Chair, to apply for the MA thesis option, you will have to submit individual application for advancement that lists the proposed committee for the thesis through CalCentral.
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 Master's 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.
Student Life
For information about graduate student life and housing options, please visit Resources & Services for Graduate Students and the Statistics Graduate Student Association.
International Students
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.
Is the MA Statistics Program a STEM OPT eligible program?
Yes, the MA Statistics program is eligible for the STEM OPT extension. The program falls under CIP code "Statistics, General 27.0501" as of July 12, 2023.