Courses - Spring 2024
EDMS451
Introduction to Educational Statistics
Restriction: Sophomore standing or higher.
Introduction to statistical reasoning; location and dispersion measures; computer applications; regression and correlation; formation of hypotheses tests; t-test; one-way analysis of variance; analysis of contingency tables.
EDMS645
Quantitative Research Methods I
Credits:
3
Grad Meth:
Reg, Aud
Research design and statistical applications in educational research: data representation; descriptive statistics; estimation and hypothesis testing. Application of statistical computer packages is emphasized.
EDMS646
General Linear Models I
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: EDMS645; or an equivalent introductory statistics course.
A first post-introductory inferential statistics course, with emphasis on analysis of variance procedures and designs from within the general linear modeling framework. Assignments include student analysis of education and related data; application of statistical software packages is emphasized.
EDMS647
Causal Inference and Evaluation Methods
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: Must have completed or be concurrently enrolled in EDMS651.
Counterfactual (potential outcomes) framework for causal inference, design/analysis strategies for confounder control, and specific best-practice applications to the evaluation of programs.
EDMS651
General Linear Models II
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: EDMS646; or students who have taken courses with comparable content may contact the department.
Multiple regression and correlation analysis; trend analysis; hierarchical and stepwise procedures; logistic regression; software for regression analysis.
EDMS722
Structural Modeling
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: EDMS657.
Statistical theory and methods of estimation used in structural modeling; computer program applications; multisample models; mean structture models; structural models with multilevel data (e.g., sampling weights, growth models, multilevel latent variable models).
EDMS724
Modern Measurement Theory
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: EDMS623 and EDMS651.
Theoretical formulations of measurement from a latent trait theory perspective.
EDMS769L
Special Topics in Applied Statistics in Education; Advanced Longitudinal Models
Credits:
3
Grad Meth:
Reg, Aud, S-F
EDMS787
Bayesian Inference and Analysis
Credits:
3
Grad Meth:
Reg, Aud
Prerequisite: EDMS779 or permission of the instructor.
Credit only granted for: EDMS769B or EDMS787.
Formerly: EDMS769B.
Models and model fitting methods commonly used in Bayesian Inference, such as Markov Chain Monte Carlo methods (e.g., Gibbs, Metropolis Sampling), with applications within and beyond the social and behavioral sciences. Analytical and philosophical differences between Frequentist and Bayesian statistics will also be highlighted.
EDMS798
Special Problems in Education
Credits:
1 - 6
Grad Meth:
Reg, Aud
Prerequisite: permission of department.
EDMS799
Master's Thesis Research
Credits:
1 - 6
Grad Meth:
S-F
EDMS889
Internship in Measurement and Statistics
Credits:
3 - 8
Grad Meth:
Reg, Aud
EDMS898
Pre-Candidacy Research
Credits:
1 - 8
Grad Meth:
Reg
EDMS899
Doctoral Dissertation Research
Credits:
6
Grad Meth:
S-F
Flagship Institution of the University System of Maryland
University of Maryland, College Park, MD 20742, USA
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301.405.1000
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