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Graduate Degree in Statistics

Overview
M.S. Degree in Statistics
The Fifth Year M.S. in Statistics
M.S. in Statistics at Newton Satellite Campus (Boston Area), Completely Flexible Program (In Person/Remote or 100% Remote), Evening Degree
Ph.D. Degree in Statistics
Data Science Certificate (possible to earn completely remotely/online)
Related Info

Overview of the Statistics Graduate Program

 

The Department of Mathematics and Statistics, offers graduate degrees in statistics at the MS and PhD levels. Note that until 2023, these degrees were granted as concentrations of the corresponding math degrees.  This page summarizes the main features of the Statistics degrees, and contains the most up-to-date information. The information on this page supersedes the information in the Axioms (Handbook), which are in the process of being updated.

The M.S. degree provides students with training in statistical applications, statistical computing and theory, preparing them for statistics and data science careers in industry, government, educational organizations, consulting firms, health care and research organizations, or for moving on to a Ph.D. in Statistics or Biostatistics. The Ph.D. degree provides a combination of theory and application preparing students for positions in academia, industry or government. The Certificate in Statistical and Computational Data Science is a joint program with Statistics and Computer Science. Each of these programs is described in more detail below.

M.S. Degree in Statistics

The M.S. program in Statistics is designed to prepare students for statistics and data science positions in industry, government, educational organizations, consulting firms, health care and research organizations. It also serves as a basis for future work towards a Ph.D. in Statistics or Biostatistics. This program is designed to provide the student with a background in basic theory along with experience in various applications, including computational aspects. As part of their training, students will receive comprehensive exposure to popular statistical software packages. In addition to courses offered within the department, the program allows room for the students to take statistics courses in other departments on campus.

Prerequisites: Students entering the M.S. program are expected to have had Linear Algebra and Calculus up through Multivariate Calculus (this is typically covered by a three-semester sequence in U.S. schools).

The requirements for the M.S. degree in Statistics involve coursework, a project and consulting or qualifying exams.

Courses

The student must complete 30 hours of coursework with grades of C or better, including at least 24 hours with grades of B or better (pass or fail grades cannot be used to satisfy this requirement). In addition, the student must have at least an overall B average.

The required 30 hours must include

  1. Stat 625: Regression Modeling,
  2. Stat 607-608: Probability and Mathematical Statistics I, II,
  3. Stat 535: Statistical Computing,
  4. At least five other courses which are either Statistics courses numbered 526 or above, from within the department, or some courses outside the department numbered 500 and above subject to prior approval by the Statistics coordinator (pre-approved list below).

 

Consulting or Basic Exam

Students completing the M.S. program in Statistics are required to either complete at least one credit of statistical consulting (typically STAT 598C) or pass two of three basic exams we offer: applied statistics, probability, and statistics, which are based on ST625 and ST535, ST607, and ST608, respectively. The Basic Exam is given twice a year, in January and in August.

Project

The project is completed under the guidance of a faculty member. This project must have prior approval of the Statistics coordinator and involves 3 credit hours which may be used to satisfy the 30 hour coursework requirement. The project can take many forms; an expository report on a particular area, an examination of methods through simulations or a detailed statistical analysis of real data. A final report is required. This requirement is typically satisfied by the successful completion of the project seminar course Stat 691P.

The Fifth Year M.S. in Statistics

This section explains how a UMass Amherst or Five College student can complete the M.S. degree in Statistics in a fifth year.

Entering the fifth year M.S. in Statistics

In order to enter the fifth year M.S. in Statistics program, students need to

  1. Start taking graduate courses (500-level or higher, as required by the UMass Amherst Graduate School) in the fall of their senior years, typically Stat 535, Stat 607, Stat 608, and/or Stat 625. Since
    1. a maximum of 6 credits can be counted toward both the M.S. in Statistics and the baccalaureate degree, and
    2. at most 12 credits of graduate work taken while enrolled as an undergraduate (6 double-counted and an additional 6 taken above and beyond undergraduate degree requirements) may be counted toward the M.S. in Statistics,
    students who would like to pursue the fifth year M.S. in Statistics should prepare to take at least 126 total credits (120 for the baccalaureate degree, up to 6 double-counted graduate credits and an additional 6 graduate credits) by the end of their senior year. (Note:  taking fewer than 12 credits is permitted to pursue the M.S. in Statistics, but taking the full 12 makes for the smoothest path to completing the MS in 1 year. Additionally, students who are pursuing a dual degree should plan on completing over and above 150 credits instead of 120). Information about the transfer of credits from undergraduate to graduate is available on the Graduate School's website.
  2. apply in their senior years to the Accelerated M.S. program in Statistics program by following instructions here.

Finishing the fifth year M.S. degree in Statistics

After being accepted into the program, students

  1. need to take additional 18 credits and fulfill the requirements for the regular M.S. degree in Statistics in the fifth year (if transferring in all 12 allowable credits from the undergraduate record; otherwise the additional credit count may be higher)
  2. may use courses taken as an undergraduate to fulfill the requirements of the M.S. degree in Statistics, although no more than 12 credits may be counted toward the M.S. degree in Statistics. For example, if a senior takes all four Stat 535, Stat 607, Stat 608, and Stat 625 graduate courses and does not apply more than 6 credits to requirements for their baccalaureate degree, they can be used to satisfy requirement for the M.S. degree in Statistics. 
  3. are not obligated to finish the program in the fifth year, although financial assistantship, if any, is only guaranteed for the fifth year

Please note that students who are interested in the fifth year M.S. program in Statistics should start planning during the fall of the their junior year and contact the Coordinator of the Statistics Program if there are any questions. To process the transfer of credits from undergraduate to the graduate degree, students must submit a Transfer of Credit form. This may be submitted to Kaitlyn O'Konis, Graduate Program Manager, at kokonis@umass.edu.

M.S. in Statistics at Newton Satellite Campus (Boston Area), Completely Flexible (In Person/Remote or 100% Remote)

-For information regarding this program, please see the following link.

-A 100% Remote Option is available for this program.

http://people.math.umass.edu/~conlon/statmtida/

-Note: non-degree students can register for graduate Statistics courses at Newton Mount Ida starting one week before the beginning of classes each semester. See:

http://www.umass.edu/graduate/apply/non-degree-students

Ph.D. Degree in Statistics

The Ph.D. degree in Statistics prepares students for academic positions or positions in Academia, or as applied statisticians in industry or government. Entering students are expected to have had Linear Algebra, Calculus and Advanced Calculus. Typically an incoming student in the Ph.D. program in Statistics will have had an introductory course or two in Statistics at the undergraduate level. Student seeking the Ph.D. degree in Statistics must complete the following: coursework, qualifying exams, language requirement and dissertation.

Coursework

  1. The student must complete successfully 36 hours of coursework, including Math 523 (or Math 623, or Math 605), Stat 535, 607, 608, 625, 705, and 725.
  2. The student must also complete five elective courses, including two 600 level statistics courses, and 3 courses of the student’s choice, which require prior approval by the statistics coordinator (pre-approved list below).

Qualifying Exams

There are two tiers of exams, Basic and Advanced, which are intended to measure a student's overall mastery of standard material. The exams are administered during the week preceding each semester (August and January).

Basic Exams: The student must pass three Basic Exams at the Ph.D. level: the Applied Statistics exam, and the Basic Probability and Basic Statistics exams, which cover the material from Stat 535 and Stat 625, Stat 607 and Stat 608 respectively.

Advanced Exams: The student must pass the Advanced Exam in advanced statistics and the oral literature-based exam. The advanced statistics exam version I is based on advanced topics in Stat 607 and Stat 608, and topics from Stat 705. The advanced statistics exam version II is based on advanced topics in Stat 607 and Stat 608, and topics from Stat 725. The two versions are offered in alternate years depending which of Stat 705 and Stat 725 is offered in a year.

For the literature-based exam, students need to choose a topic from the list of topics in the Axioms and form an exam committee that includes the primary faculty of that topic and two secondary faculty. Students are then given reference papers on the chosen topic to read. The exam is in the form of oral presentation and responding questions in front of the exam committee. A student may select a non-standard exam topic, in which case, the student must have the agreement of their committee members on the topic and the reading list.

In order to take the literature-based exam, a student is responsible for forming an exam committee by the end of September for a January exam, or by the last day of spring classes for an August exam. Decisions on passing the exam are by unanimous consent of the exam committee. A student who does not pass will have one more chance to pass the literature-based exam. The second attempt may be on the same or a different topic.

Dissertation

After passing the Advanced Exam, the student becomes a Ph.D. in Statistics candidate. The student must write a satisfactory dissertation and pass a final oral examination (primarily a defense of the dissertation), and must satisfy all other requirements of his or her dissertation committee. The student is required to register for a minimum of 18 dissertation credits.

Data Science Certificate (possible to earn completely remotely/online)

The Certificate in Statistical and Computational Data Science is offered jointly between Statistics and Computer Science. The Certificate can be completed in one year and requires 5 courses total, with a minimum of 2 courses in each of Statistics and Computer Science.

It is possible to earn the Certificate completely remotely/online; please see the following link: https://people.math.umass.edu/~conlon/statmtida/datascience.html

For more information on the Certificate, please see the following link:

https://ds.cs.umass.edu/academics/certificate-data-science

Approved Courses Outside the Department

The following courses are pre-approved to count toward STAT MS and PhD degrees (as specified) without additional prior approval.  Please contact the Statistics Coordinator for pre-approval of any other courses outside the department.

Toward MS Degree only:
    * PHYSICS 597D (ST- Topics in Statistics and Data Analysis)     * COMPSCI 514 (Algorithms for Data Science), CS 590V (Data Visualization and Exploration)     * Biostats 597D, Biostats 650, Biostat 690Z  

Toward MS or PhD degree:     * CS589 (Machine Learning), CS 682 (Neural Networks), CS 688 and CS690OP, CS 690D, CS 696DS, CS 611 (Advanced Algorithms), COMPSCI 688 (PROBABILISTIC GRAPHICAL MODELS),     * Biostat 683/Biostat 690B (intro to causal inference), Biostat 690T (Applied Statistical Genetics), Biostat 730, Biostat 740 (Analysis of Mixed Models Data), Biostat 743 (Categorical), Biostat 748 (Applied Survival Analysis), Biostat 749 (Clinical Trials), Biostat 750 (Applied Statistical Learning), Biostat  790A,     * Psych 891FM     * PoliSci 797TA (Text as Data)

 

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