Program type:


On Campus
Est. time to complete:

1-2 semesters
Credit Hours:

Position yourself as the go-to data expert in your organization.
Data analysis capacity and quantitative skills are valuable assets to many doctoral students across a variety of fields. This minor is designed to provide advanced quantitative skills and experiences, particularly in applied social science research areas.

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Why Earn a Research, Measurement and Statistics Minor?

Students take 12 hours of advanced course work in the research, measurement and statistics concentration area in the Department of Educational Psychology.

This minor allows doctoral students to document and market their capacity in quantitative methods along with their regular major area.

Research, Measurement and Statistics Minor Highlights

Hone research methodology and data analysis skills to inform policy-making in education and other critical areas.
Develop data-driven skills to improve organizational decision-making and conduct vital evaluations to examine processes and outcomes.
Use advanced data analysis and statistical expertise to improve evidence-based organizational decision-making and practices.
All course instruction is provided in the evening hours.
Flexibility in the course schedule is provided to accelerate students through the program or permit students to take courses at a pace that allows the program to fit with busy family and/or work lives.
Develop and evaluate different educational and psychological phenomena.

Research, Measurement and Statistics Minor Courses You Could Take

Multivariate Statistics in Education (3 hrs)
History of multivariate statistics, univariate vs. multivariate statistics, matrix algebra, multivariate analysis of variance, canonical correlation, discriminant analysis and multivariate analysis of contingency tables.
Statistical Theory and Simulations (3 hrs)
Statistical theory and simulation of statistical distributions. Topics include factors affecting sampling distributions, sampling from different distributions, Chebyshev’s theorem, Central Limit Theorem, probability distributions, statistical distributions (normal, t, chi-square, correlation, regression), Power (sample size, Type I error, Type II error, confidence interval, effect size), Monte Carlo, meta-analysis, bootstrap and jackknife techniques.
Advanced Testing and Measurement (3 hrs)
History of testing and assessment as related to education and psychology, standards for educational and psychological testing, and conceptualization of constructs and latent variables. Classical Test Theory, including procedures for item analysis, estimating reliability and validity in the construction of norm-referenced and criterion-referenced tests. Generalizability theory, including multiple sources of measurement error in simple and higher order designs for both G- and D-studies
Multiple Regression Analysis and Related Methods (3 hrs)
Introduction to and application of multiple regression and related methods to analysis of data from correlational and experimental studies in education and related disciplines. Topics include introduction to the general linear model, simple and multiple linear regressional analysis, data inspection and transformation, non-linear regression, trend analysis, cross validation procedures and utilization of statistical software for conducting regression analyses.

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