Courses - Spring 2023
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.
EDMS769T
Special Topics in Applied Statistics in Education; Topics on Machine Learning
Credits:
3
Grad Meth:
Reg, Aud, S-F
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
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