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  • Steven LeMire
Portrait of Steven LeMire

Steven LeMire

  • Assoc. Professor, Education, Health & Behavior

Contact Info

  • Email: steven.lemire@UND.edu
  • Office: 701.777.3158
  • Dept:

Office Address

Education Building Room 356
231 Centennial Drive Stop 7189
Grand Forks ND 58202-7189

EFR 509 Introduction to Research Methodologies. The course covers quantitative as well as qualitative types of research. The paradigms of both types of research will be contrasted and the application of the methodologies in actual research investigated.

EFR 513. Large Dataset Management and Analysis. 3 Credits. A study of educational and social science statistics involving gathering, managing, manipulation and analysis of large data sets, both local and national, using SPSS and/or SAS. Prerequisite or Co requisite: EFR 515 or consent of instructor

EFR 515 Statistics I. 3 Credits. An introduction to basic statistical methods, focusing primarily on descriptive statistics and inferential statistics up to and including one-way analysis of variance.

EFR 516. Statistics II. 3 Credits. An in-depth study of inferential statistics with primary emphasis on analysis of variance models, multiple regression techniques, analysis of covariance and other higher-order statistical procedures. Prerequisites: EFR 515 or consent of instructor.

EFR 517. Advanced Research Methodologies. 3 Credits. Both qualitative and quantitative aspects of research are considered for a variety of topics, including ethics in research, use of data banks, Q-methodology, survey research, Bayesian concepts, critical theory, longitudinal research and research consultation. Comprehensive examinations in educational research are addressed. This is a capstone course in educational research. Previous or concurrent involvement in research is highly desirable. Available for doctoral level students only.

EFR 518. Multivariate Analysis. 3 Credits. Multiple regression in generalized problem solving; discriminant analysis, factor analysis, multivariate analysis, canonical analysis, and multivariate analysis of covariance. Students are encouraged to analyze their own data including student-generated computer applications.

Type I error Rate

Large Educational Data Sets

SAS Programming 

School Data

LeMire, S. D., Achtenberg, L., & Opp, D. (2018). Leadership Development for High School Students in a Summer Performing Arts Program. Journal for Learning through the Arts: A Research Journal on Arts Integration in Schools and Communities. Volume 15(1).

https://escholarship.org/uc/item/5061b1jn

Video of SPA program

https://www.youtube.com/watch?v=lUfVpnsIm-w&feature=emb_logo

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