Master of Science (M.S.) in Applied Statistics and Psychometrics

Master of Science (M.S.) in Applied Statistics and Psychometrics

Demand is at an all-time high for data analysts who can help organizations, technology companies, governments, and nonprofit agencies grasp their organizational, societal, and scientific needs. The value of understanding and supporting evidence-based decision-making is essential. The STEM M.S. in Applied Statistics and Psychometrics program prepares you to respond to today’s “new normal” with a depth and breadth of statistical expertise that will serve you, your employers, and your partners well. You will graduate ready to conduct a wide range of advanced statistical analyses with a grounding in the burgeoning field of psychometrics.

At a Glance

How many courses?

The program consists of 10 courses (30 credits). 

How long will it take?

Students spend 2–3 years pursuing the program on a full-time or part-time basis.

When can I start?

You can begin the program in the spring, summer, or fall semester.

What Is Psychometrics?

Psychometrics is the field of science associated with the development of quantitative instruments, such as tests and psychological scales, that measure knowledge, skills, and attributes.

Why the M.S. in Applied Statistics and Psychometrics?

In comparison to the M.S. in Data Science, this program has a stronger curriculum in applied statistics, with three required courses in topics such as educational measurement and psychometrics. Some objectives are shared with the M.S. in Data Science, but with different emphases.


During this program, you will:

    be exposed to the latest trends in psychometric theory and research

    build applied skills in complex data so you can conduct psychometric analyses

    complete a hands-on internship with organizations such as Facebook, Cognia (Measured Progress), ACT, Aetna Health, or ETS

    join a community committed to using evidence-based research to foster organizational, educational, and behavioral improvement and equity


    • Courses: 10
    • Credits: 30
    • Comprehensive Exam
    CourseCourse TitleCredit

    Instrument Design and Development 

    This course is designed to familiarize students with the strategies, techniques, tactics, and issues in the development and administration of survey instruments. It will emphasize theoretical, measurement and practical considerations in the development of attitudinal instruments. The development and analysis of data resulting from several types of measurement scales will be covered.


    Intermediate Statistics 

    Topics and computer exercises address tests of means, partial and part correlations, multiple regression, analysis of variance with planned and post hoc comparisons, analysis of covariance, repeated measures analysis, elements of experimental design, and power analysis.


    Introduction to Mathematical Statistics

    Quantitative methods in educational and psychological research have become increasingly complex over time, employing more sophisticated models and estimation strategies. This course helps students to develop a deeper understanding of the strengths and limitations of different approaches to inference and to appreciate some of the ongoing arguments among the adherents of the different philosophies regarding statistical inference.


    Psychometric Theory: Classical Test Theory and Rasch Models

    Presents a study of theoretical concepts, statistical models, and practical applications in educational and psychological measurement. General topics include the history of measurement, Thurstone and Guttman scales, classical true-score theory, and item response theory. Specific topics include principles of Rasch measurement, parameter estimation procedures, fit statistics, item banking, and computer adaptive testing.


    Psychometric Theory II: Item Response Theory

    This course presents an advanced study of theoretical concepts, statistical models, and practical applications in educational and psychological measurement. Topics include item response theory, two-parameter model, three-parameter model, methods for estimating latent trait and item parameters, models for polytomously scored items, differential Item Functioning(DIF), test equating , vertical scaling, computerized adaptive testing, standard setting, and multidimensional item response theory models. The IRT software or tools used in this course include R, IRTPRO, BILOG-MG, PARSCALE, NOHARM, DIF related software, STUIRT, ST., EQUATE, etc.


    General Linear Models 

    Addresses the construction, interpretation, and application of linear statistical models. Specifically, lectures and computer exercises cover ordinary least squares regression models; matrix algebra operations; parameter estimation techniques; missing data options; power transformations; exploratory versus confirmatory model building; linear-model diagnostics, sources of multicollinearity; diagnostic residual analysis techniques; variance partitioning procedures; dummy, effect, and orthogonal coding procedures; and an introduction to structural equation modeling.


    Multivariate Statistical Analysis

    This course provides lectures, examples, and lab analyses that address multinomial and ordinal logistic regression models, multiple group discriminant analysis, cluster analysis, multivariate analysis of variance, principal component analysis, factor analysis, and structural equation modeling. We cover various issues related to research design, model building, and the interpretation of the output from SPSS, R, Lisrel, and SAS software programs.


    Multilevel Regression Modeling

    This course introduces students to multilevel regression modeling (aka hierarchical models or mixed effects models) for analyzing data with a nesting or hierarchical structure. We discuss the appropriate uses of multilevel regression modeling, the statistical models that underpin the approach, and how to construct models to address substantive issues. We consider a variety of types of models, including random intercept, and random slope and intercept models; models for longitudinal data; and models for discrete outcomes. We cover various issues related to the design of multilevel studies, model building and the interpretation of the output from HLM and SPSS software programs.


    Students will select 2 electives (3 credits each) with the help of their advisor. 

    CourseCourse TitleCredit

    Master's Comprehensive Exam

    In order to ensure that all students graduating from the master's program have a fundamental understanding of the field which they are about to enter, they are required to complete a written comprehensive examination covering the broad areas of the core courses. 

    Boston College has established a strong local network and alumni network, and we have very good internship and job placement. There are nearly limitless things you can do with a stats background.
    Zhushan “Mandy” Li, Ph.D., Program Director, M.S. in Applied Statistics and Psychometrics


    Internationally recognized faculty integrate interdisciplinary theory with the most current evidence-based practices.

    Financial Aid

    Education should level the playing field. We feel the same way about financial aid.

    The Lynch School of Education and Human Development provides more than $11.4 million in financial aid to students each year. As a result, the quality of BC’s instruction, the benefit of our alumni network, and the impact a BC degree will have on your employment options is both affordable and invaluable. 

    MESA Research Centers 

    Both master’s and doctoral students can work with faculty and other experts at one of the Lynch School’s internationally renowned MESA‐affiliated research centers:

    TIMSS and PIRLS International Study Center

    The Center conducts comparative educational achievement studies in math and science (the Trends in International Mathematics and Science Study or TIMSS) and reading (Progress in International Reading Literacy Study or PIRLS) under the auspices of the International Association for the Evaluation of Educational Achievement. 

    Center for the Study of Testing, Evaluation, and Educational Policy (CSTEEP)

    CSTEEP is an educational research organization that conducts research on testing, evaluation, and public policy, working with individual schools, districts, states, and countries to advance educational testing practices and policy and improve the quality and fairness of education.



    • Researcher
    • Assistant Professor
    • Project Analyst
    • Research Associate
    • Director of Efficacy Analytics and Studies
    • College President
    • Principal Psychometrician
    • Director, Innovation Lab
    • Senior Vice President of Research
    • Senior Consultant


    • American Institutes for Research
    • Northern Illinois University
    • Bank of America Operations
    • Hanover Research
    • Pearson
    • Cumberland County College
    • ACT Inc.
    • Measured Progress
    • Maguire Associates
    • Sheffield Research and Evaluation

    Alumni Profiles




    Application & Deadlines

    Apply Now

    A non-refundable application fee of $75 is required. The fee is waived for select applicants.


    Spring 2024

    Priority Deadline - November 1
    Rolling Admission - Until Dec 1

    Summer 2024

    Priority Deadline - January 4
    Rolling Admission - Until April 5 

    Fall 2024

    Priority Deadline - January 4
    Rolling Admission - Until July 15


    To be uploaded to your online application.

    In addition to your academic history and relevant volunteer and/or work experience, please include any licenses currently held, any social justice-related experience, any language skills other than English, and any research experience or publications.

    Personal Statement

    To be uploaded to your online application.

    In 1,000-1,500 words, describe your academic and professional goals, any experience relevant to this program, and your future plans, expectations, and aspirations.

    Letters of Recommendation

    Two letters of recommendation are required, with at least one preferably coming from an academic source. Applicants may submit one additional recommendation of their choice.


    Transcripts from all college/university study are required.

    Applicants who have received degrees from institutions outside the United States should view the "International Students" section for additional credential evaluation requirements.

    Please begin your online application before submitting your transcripts. Details on how to submit transcripts and international credential evaluations can be found within the application. In order to ensure your transcript reaches our office, it is important to review and follow the instructions.

    Standardized Tests

    GRE scores are not required. If you wish to send GRE scores, the Lynch School GRE code is 3218.

    Please view the "International Students" section for information on English Proficiency test requirements.

    Writing Sample

    Not required.

    International Students

    Applicants who have completed a degree outside of the United States must have a course-by-course evaluation of their transcript(s) completed by an evaluation company approved by the National Association of Credential Evaluation Services (NACES). Submission of falsified documents is grounds for denial of admission or dismissal from the University.

    Applicants who are not native speakers of English and who have not received a degree from an institution where English is the primary language of instruction must also submit a TOEFL or IELTS test result that meets the minimum score requirement.

    Please click the link below for full details on these requirements.

    Requirements for International Students

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