Research Methodology Seminars
Developing Research Skill
Doctoral candidates complete four research methodology seminars. These seminars enable you to design, conduct, and evaluate business research. All candidates must complete a graduate elementary statistics course within three years before or one year after starting the doctoral program. To satisfy this prerequisite, you may register for DPS 070 at Pace University or for a similar course at another university.
Explorations in Business Research
Exposes students to a wide variety of research approaches across many disciplines. Explores the processes and problems of designing and conducting various kinds of research. Develops skill in evaluating business research. Through a series of guest researchers, enables students to discuss research process and publication issues with experts.
Research Design and Measurement
Explores the non-statistical issues in research planning and execution. Develops understanding and skill in the scientific approach, problem definition, hypothesis development, research design, and methodology planning. Examines techniques like measurement approaches, scale construction, interview procedures, questionnaire design, secondary sources, observational capability, content analysis, and experimental design. Analyzes problems of assessing reliability and validity of research findings.
Data Analysis with Regression
Enables doctoral students to apply regression analysis to empirical data. Rigorously reviews the theory of regression analysis. Identifies the types of research problems and data structures appropriate for regression analysis. Applies regression to a variety of business areas and problems so students can gain an applications-guided understanding of regression analysis theory. Includes topics of model specification, significance determination, nonlinear transformations, residual analysis, normality assessment, and outlier analysis, plus more advanced topics including autocorrelation, multicollinearity, heteroscedasticity and extrapolation. Requires use of SPSS statistical software to analyze data with regression analysis.
Data Analysis with Selected Multivariate Methods
Equips students with the skills needed to analyze data for advanced research using selected multivariate statistical techniques like factor analysis, discriminant analysis, cluster analysis, analysis of variance, and structural equation modeling. Emphasizes the selection, application, and interpretation of statistical techniques rather than the mathematical theory that underlies them. Requires SPSS statistical software to analyze data.