Carnegie Mellon University

Master of Statistical Practice

Carnegie Mellon University's premier professional training in data science program.

The Master of Statistical Practice (MSP) is a one-year, two-semester professional master's degree program emphasizing competencies in three main areas of focus: Data Analysis, Statistical Computing, and Professional Skills.

The primary focus of the MSP program is developing industry-valued competencies in our students. Our program attracts students desiring a career in a fast-paced, high-growth field. Students who are an ideal fit for the MSP are looking to immediately work in industry in the United States immediately following graduation. MSP graduates have successfully gained positions as data scientists, data analysts, and data engineers in diverse industries such as banking, sports, health care, government, and tech.

What Do Alumni Have To Say?

"One thing that I feel is worth highlighting is the consulting project, as it was a unique experience that helped a great deal in developing our statistical thinking skills. Given a research question and a data set, we thought through each aspect of the analysis, from cleaning the data, deciding what methodology to use, doing the analysis and presenting the results. These are skills that are applicable to working in industry, as many jobs (including mine) are project-based."

"I think the MSP program is a unique program that not only prepares you for the practical statistical analysis experience that gives you a significant edge on the job market, but also teaches you theoretical knowledge necessary for you to go above and beyond on your own later in your professional career."

"I learned to first understand the problems, check assumptions and apply statistical knowledge to solve real world problems. And also I was trained to work on projects as a team, write reports about the analysis and finally give presentations based on the results we got. As a result, I am not only able to use statistics to solve problems in sciences but also in various kinds of fields such as education, clinical trials and so on."

Frequently Asked Questions

Students who are an ideal fit for the MSP are looking to work in industry in the United States immediately following graduation. MSP graduates have successfully gained positions as data scientists, data analysts, and data engineers in diverse industries such as banking, sports, health care, government, and tech. The MSP will not only build foundational skills computing and analytic skills in demand, it is intended to assist students in identifying and focusing on industries and positions relevant to their aptitudes and interests, navigating the job market, and positioning graduates to successfully navigate careers post-graduation.

There are a variety of programs at CMU for students who are interested in related specific statistical graduate study topics and related outcomes. The Master of Science in Computational Finance (MSCF) is a program for students specifically interested in quantitative finance, and the Master of Science in Machine Learning is a program for students specifically interested in advanced study in Machine Learning.

    • Two semesters of calculus based probability and mathematical statistics
      Topics should include: random variables, distribution functions, joint and conditional distributions, functions of random variables & their probability distributions; maximum likelihood estimation, properties of estimators, hypothesis testing, interval estimation.

      Typical Textbook: Mathematical Statistics with Applications - Wackerly, et al. or equivalent
      CMU classes are: 36-225 and 36-226
    • One course in linear regression analysis
      Topics should include: exploratory data analysis, linear regression models, validation and interpretation of models

      Typical Textbook: Applied Linear Regression Models - Kutner, et al. or equivalent. A good Econometrics course is an acceptable substitute.
      CMU classes are: 36-401
  • One course in matrix algebra

The tuition for the MSP program for the 2022-2023 academic year is $54,450 plus mandatory student fees of approximately $980.

The following courses are core curriculum requirements of the MSP program. Please see the Schedule of Classes to view the course descriptions.

Fall Curriculum 

  • 36-611: "Professional Skills for Statisticians I" 
  • 36-613: “Data Visualization”
  • 36-614: “Data Engineering and Distributed Environments” 
  • 36-617: "Applied Linear Models" 
  • 36-650: "Statistical Computing" 

Spring Curriculum

  • 36-612: "Professional Skills for Statisticians II" 
  • 36-615: “Software for Large-Scale Data”
  • 36-616: “Computational Methods for Statistics”
  • 36-618: "Time Series & Experimental Design" 
  • 36-726: "Statistical Practice"
  • In addition to the core curriculum requirements, students must complete an elective course in both the Fall and Spring semesters. Electives are offered on a rotating basis; some past topics include:
  • 36-661: "Statistical Methods in Epidemiology"
  • 36-662: "Methods of Statistical Learning”
  • 36-663: "Multilevel and Hierarchical Models"
  • 36-664: "Applied Multivariate Methods"
  • 36-666: "Statistical Methods in Finance"
  • 36-667: "Data over Space & Time"
  • 36-668: "Text Analysis”

MSP students are typically not permitted to take courses outside of the Department of Statistics & Data Science. Normally, all the MSP students take core requirements together as a cohort. Electives are offered on a rotating basis. Alternative courses within the Department of Statistics & Data Science may be allowed as a substitute should a comparable course of study already have been successfully completed prior to entry into the MSP program — any substitutions are considered on a case-by-case basis and must be approved by the Department of Statistics & Data Science.

We do not offer a financial aid package for the MSP program. Subject to eligibility and qualifications, MSP students will receive the offer to work as an educational assistant or teaching assistant in the Department of Statistics & Data Science. MSP students receive a stipend for their role as an educational assistant or a teaching assistant.

The application fee for the MSP program is $60 from October 3rd, 2022 through November 4th, 2022, and $75 from November 5th, 2022 through January 15th, 2023. The application deadline is Sunday, January 15th, 2023 at 11:59 pm EST.

Please email msp-admissions@stat.cmu.edu if you have any questions or concerns about the application fees or the application payment method. The online application system accepts payments via credit card only. Please be advised that we do not accept cash.

All non-native English speakers are required to submit valid, non-expired TOEFL scores. A desirable total TOEFL score is 105 or higher. Speaking TOEFL scores should be at least 28. IELTS is also acceptable, with a desirable speaking score of at least 9.

Institution Code: 2074
Department Code: 59

All non-native English speakers are required to submit valid, non-expired TOEFL scores. Current IELTS scores are also acceptable. Applications without TOEFL (or IELTS) will not be considered. We will not accept expired scores or waive test scores.

TOEFL scores are valid for 2 years from the date of the exam.

Institution Code: 2074
Department Code: 59

While we require a GRE score with your application submission, we are interested in the student's entire application package, including coursework, statement of purpose, and recommendations. Our institution and department codes are as follows:

Institution Code: 2074
Department Code: 0705

Three, at least two of which should be faculty recommendations.

Incomplete applications will not be eligible for review by the admissions committee.

The application deadline is Sunday, January 15th, 2023 at 11:59 pm ET. We will not accept submissions after this deadline. We also do not accept paper submissions or paper supplemental materials.

The number of admitted applicants varies by years based on applications received and capacity available. Over the prior three years, we have admitted on average between 10% and 15% of program applicants.

Students are prepared for the job market through a plethora of outlets interwoven throughout the MSP program including, but not limited to, the following: The curriculum specifically focuses upon the computing skills, statistical application/theory, & professional skills necessary to be successful in data science and statistical consulting positions. We review and help edit students' résumés, cover letters, LinkedIn profiles, etc., and practice the skills necessary to perform well in both technical and behavioral interviews. Additionally, the MSP frequently pairs with the CMU Career & Professional Development Center (CPDC) and the Global Communication Center (GCC) to complement, amplify, and practice communication skills throughout the program. Guest speakers, company recruiters, & current professionals across industry verticals are often invited to discuss the day-to-day experiences and insights of active data scientists and statistical consultants. The MSP also fosters an alumni network and an internal job/internship board where opportunities are shared among and across cohorts.

Every year, approximately >90% of students land a job within the field of statistics & data science or matriculate into a Ph.D. program within 90 days of graduation. Recent surveys by the Carnegie Mellon University Career and Professional Development Center show the wide variety of offers our students receive upon graduation. Currently reported outcome data is available.