The Master of Science in Applied Statistics and Psychometrics meets the need for quantitative specialists to conduct statistical analyses, design quantitative research studies, and develop measurement scales for educational, social, behavioral, and health science research projects.
Employers and doctoral programs in education, psychology, social work, nursing, and sociology are seeking graduates trained in technical quantitative analysis. Federally funded and nonprofit agencies have set rigorous expectations in research methodology and data analysis for the studies they fund.
Students also benefit from multiple opportunities to engage in hands-on research. In addition to being asked to support the active research of our faculty, Boston College is also home to a number of internationally renowned research centers.
Understand the theory of applied statistics and psychometrics
Conduct analyses using advanced procedures such as multiple regression, multivariate models, hierarchical linear modeling, causal modeling, and longitudinal analyses
Interpret and report quantitative and qualitative designs, procedures, and results
Design, conduct, analyze, interpret and report both Classical Test Theory and Item Response Theory analyses
Education should level the playing field – we feel the same way about financial aid.
The Lynch School of Education provides more than $7.5 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. Here’s why:
This program consists of 10 courses for a total of 30 credits.
Students will typically complete the program between 2-3 years.
Students can begin the program in the spring, summer, or fall semesters.
Students can enroll full-time or part-time for this program.
Topics and computer exercises address tests of means and proportions, partial and part correlations, chi-square goodness-of-fit and contingency table analysis, multiple regression, analysis of variance with planned and post hoc comparisons, 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.
General Linear Models
Addresses the construction, interpretation, and application of linear statistical models. Specifically, lectures and computer exercises will cover multiple regression models; matrix algebra operations; parameter estimation techniques; missing data; transformations; exploratory versus confirmatory models; sources of multicollinearity; residual analysis techniques; partial and semipartial correlations; variance partitioning; dummy, effect, and orthogonal coding; analysis of covariance; and logistic regression.
Multivariate Statistical Analysis
Provides lectures, examples, and student analyses that address multiple group discriminant analysis, classification procedures, principal components and common factor analysis, and multivariate analysis of variance.
Psychometric Theory: Classical Test Theory and Rasch Models
Introduces psychometric theory, selection, and use of standardized aptitude, ability, achievement, interest, and personality tests in the counseling process from a social justice perspective. Includes measurement concepts essential to test interpretation, and experience in evaluating strengths, weaknesses, and biases of various testing instruments. Students will gain laboratory experience in administration, scoring, and interpretation of psychological tests.
Psychometric Theory II: Item Response Theory
This course continues the examination and application of the principles of item response theory and educational measurement introduced in previous courses. The first section of the course will address the use of a variety of item response theory models for dichotomous and polytomous items. The second section of the course will focus on application of the principles of item response theory to a variety of practical situations and problems commonly encountered in educational testing. In the final section of the course, overarching theoretical and practical issues are addressed and future directions in item response theory are discussed.
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.
|ERME 8100||Master’s Comprehensive Examination||0|
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Director, Innovation Lab
Senior Vice President of Research
Career paths chosen by previous graduates of the MESA Department.
In addition to your academic history and relevant 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.
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.
Identification of recommenders/instructions to recommenders are outlined in the online Application Form.
Three letters of recommendation are required with at least one required from an academic source. Applicants with significant relevant professional experience may submit additional recommendations from supervisors.
Undergraduate transcripts are required as part of the application process and graduate transcripts are accepted, but not required. Please note the following:
Transcripts must be mailed to the following address:
Boston College, Lynch School of Education
Office of Graduate Admission, Financial Aid, and Student Services
Campion Hall 135
140 Commonwealth Avenue
Chestnut Hill, MA 02467
For all Boston College students and alumni
If you received any type of degree from Boston College, or if you are a current Boston College student, the GRE is not required.
For all other applicants
If you did not receive a degree from Boston College or if you are not a current Boston College student, the GRE is required.
The Lynch School GRE code is 3218.