{"id":2602,"date":"2025-04-23T10:57:31","date_gmt":"2025-04-23T14:57:31","guid":{"rendered":"https:\/\/www.bu.edu\/mssp\/?page_id=2602"},"modified":"2026-06-30T12:13:46","modified_gmt":"2026-06-30T16:13:46","slug":"academics","status":"publish","type":"page","link":"https:\/\/www.bu.edu\/mssp\/academics\/","title":{"rendered":"Academics"},"content":{"rendered":"
Academics<\/h6>\n

Program Overview<\/strong><\/p>\n

The Master of Science in Statistical Practice (MSSP) is designed for students who want to acquire fundamental training in statistics and how it is applied in fields like economics, education, law, management, science, and social science, to real world problems. In addition to students with traditional undergraduate training in statistics and mathematics, it is also suitable for students with backgrounds in fields like biology, bioinformatics, economics, management, neuroscience, psychology, and various areas of engineering. The program requires 32 credits (8 courses), which can be completed in as little as 1 year as a full-time student.<\/p>\n

\n\n\n\n
\n

2<\/p>\n

PRACTICUM TERMS<\/h6>\n<\/td>\n
\n

6<\/p>\n

COURSES<\/h6>\n<\/td>\n
\n

32<\/p>\n

TOTAL CREDITS<\/h6>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

 <\/p>\n

\n
Required Courses<\/h6>\n

Essential courses that form your statistical expertise<\/p>\n

20 CREDITS (5 Classes)<\/strong><\/h6>\n\n\n\n\n\n\n\n
\n

675 \u2013 Statistics Practicum 1 **<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

676 \u2013 Statistics Practicum 2 **<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

677 \u2013 Conceptual Foundations of Statistics<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

678 \u2013 Applied Statistical Modeling<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

679 \u2013 Applied Statistical Machine Learning<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

** Two-term practicum sequence<\/strong><\/p>\n<\/div>\n

 <\/p>\n

\n
Preferred Electives<\/h6>\n

Choose three elective courses to complement your core training<\/p>\n

12 CREDITS (3 Classes)<\/strong><\/h6>\n\n\n\n\n\n
\n

520 \u2013 Applied Statistical Methods for Modern Data<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

615 \u2013 Data Science in R<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n

\n

+1 Additional Elective<\/p>\n<\/td>\n

\n

4<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

<\/p>\n

\n
<\/div>\n
\n

Why Choose MSSP?<\/h3>\n
\n
\n
x<\/div>\n

Flexible Timeline<\/h4>\n

Complete in 12 months full-time or choose flexible pacing that fits your schedule<\/p>\n<\/div>\n

\n
x<\/div>\n

34% Job Growth<\/h4>\n

Statistics-related roles projected to grow much faster than average through 2034<\/p>\n<\/div>\n

\n
x<\/div>\n

Real-World Focus<\/h4>\n

Apply theory to actual business problems through our statistics practicum<\/p>\n<\/div>\n

\n
x<\/div>\n

Industry Connections<\/h4>\n

Work directly with industry partners on impactful projects<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

Online Summer Learning Modules<\/h5>

\nStudents admitted to the MSSP program will complete online summer learning modules in the summer months prior to beginning their first semester. These modules provide review and an extension of each student’s current mathematical knowledge to ensure that you are well-prepared for the required coursework. Online summer learning modules will focus particularly on key topics from probability and linear algebra, as well as reviewing relevant aspects of calculus and basic programming. Online summer pre-preparation is an integral component of the MSSP program, and critical for building successful teams throughout the rest of the year.<\/span>
\n<\/div>\n<\/div>\n\n
Statistics Practicum<\/h5>

\nThe Statistics Practicum<\/strong><\/a> is the centerpiece of the MSSP program. Comprised of in-class instruction, hands-on consulting experience in the MSSP Consulting Services, and intensive partner projects with Boston-based organizations, the practicum provides students with an environment in which they integrate the theory, principles, and methods learned in other MSSP courses with actual practice.<\/span><\/p>\n

The Practicum isn’t just about crunching numbers. Students learn the entire consulting process, from initial client meetings to delivering insightful analyses and interactive presentations. Students gain direct and intensive experience doing the kinds of work they can expect to encounter after graduation.<\/span>
\n<\/div>\n<\/div>\n\n

Coursework<\/h5>

\nOur mantra is that theory informs principle, and principle informs practice. Coursework in Conceptual Foundations of Statistics (MA677) not only provides you with the necessary foundations in probability and statistical inference \u2014 it also shows you why they matter in practice. The toolbox of today’s practicing data scientist is filled with statistical and machine learning methods. Over just two semesters you receive exposure to a broad and rich collection of methods necessary for your success, in the courses Applied Statistical Modeling (MA678) and Applied Statistical Machine Learning (MA679). The ability to navigate the modern computing environment is critical for success as a data scientist, allowing you to combine data with theory and methods to create knowledge. Between our Data Science with R (MA615) and our Statistics Practicum (MA675\u20136), you are exposed not only to multiple software environments (e.g., R, python, SAS, SQL) but also related elements like software versioning, visualization, and reproducible research.<\/span>
\n<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

Academics Program Overview The Master of Science in Statistical Practice (MSSP) is designed for students who want to acquire fundamental training in statistics and how it is applied in fields like economics, education, law, management, science, and social science, to real world problems. In addition to students with traditional undergraduate training in statistics and mathematics, […]<\/p>\n","protected":false},"author":20263,"featured_media":2903,"parent":0,"menu_order":9,"comment_status":"closed","ping_status":"closed","template":"page-templates\/landing.php","meta":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/pages\/2602"}],"collection":[{"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/users\/20263"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/comments?post=2602"}],"version-history":[{"count":51,"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/pages\/2602\/revisions"}],"predecessor-version":[{"id":3463,"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/pages\/2602\/revisions\/3463"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/media\/2903"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/mssp\/wp-json\/wp\/v2\/media?parent=2602"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}