Doctoral Student 4: 1,690 pages read and 230 written

RESD 720 Multivariate Research Methods Yair Levy - AM

This advanced multivariate research methods course builds on the content learned in the doctoral course RESD-705, Introduction to Research Methodology for Information Systems. This data-driven doctoral course will provide the skills needed to perform advanced multivariate data analysis by incorporating currently used techniques. Topics covered will include assumptions and limitations, multivariate data collection, pre-analysis data screening, factorial and multivariate analysis of variance and covariance, linear and non-linear multiple regressions, path analysis, exploratory factor analysis, confirmatory factor analysis, and structural equation models (SEM). Students will be provided with data-sets for data analyses of the multivariate methods discussed in course along with scholarly articles that make use of the multivariate methods discussed. Students will be introduced to the use of SPSS, PLS, and other advanced multivariate tools.

DISS 885 Doctoral Research Yair Levy

The student pursues research under the direction of a faculty member. To register, students contact their advisor with the name of the faculty member under whose direction they would like to work and a brief explanation of the research area to be explored. Recommended prerequisite: completion of a 700-level course with the requested professor with a grade of B+ or higher.