- Statistical Analysis for Researchers
In quantitative research, a key step is a statistical analysis to discern meaningful patterns in the study data and relationships between variables. This course provides a foundational understanding of statistical concepts and methods for data analysis and interpretation.
Topics include principles of statistical thinking for management research; numerical and graphical tools for describing and analyzing business data; the normal distribution, populations, and sampling; confidence intervals, hypothesis testing; correlation coefficients, and simple linear regression. (2–4 credits)
- Introduction to Multivariate Data Analysis
This course provides a conceptual introduction to the multivariate statistical methods most commonly used in management research in order to prepare students to critically read the quantitative management research literature and begin preparation of their own dissertation research proposal. Topics include: review of simple linear regression and correlation, multiple regression, logistic regression, discriminant function analysis, univariate comparison of means (analysis of variance), multivariate analysis of variance, principal components and factor analysis, path analysis and structural equation modeling, and multilevel modeling. (4 credits)
- Multiple Regression
This course examines contemporary procedures of applied multiple regression analysis for business data. Topics include: review of simple regression, hypothesis tests and confidence intervals, modeling nonlinear regression relationships, model specification strategies, diagnostic testing of model adequacy, robust regression, categorical explanatory variables, outliers and influential observations, path analysis, and logistic regression. (4 credits)
- Quantitative Research Design
This introductory course begins with the logic of causation and correlation in social science. We review the steps of scientific inquiry: literature review, theory development, operationalization and measurement of variables, data collection and analysis, interpretation, and write-up. Experimental and quasi-experimental research designs are treated specifically. Topics include: the types of validity, the “control” of extraneous influences by design or by statistical methods, and the relationship between research design and statistical testing. (4 credits)
- Qualitative Research Methods
Qualitative research is often used in research on complex behavioral systems and in the exploration of a new field of study. Using methods such as participant observation, unstructured interviewing, and the examination of documents, a scholar can form theories that may be later tested by quantitative methods or validated on other samples. Particular attention is given in this course to the methodology of grounded theorizing in multiple case studies and problems of data analysis, interpretation, and generalization. (4 credits)
- Survey Design
In this course, students learn the essential elements of developing, analyzing, and validating a survey instrument. The course will explore the options available to the researcher, examine the decisions to be made in designing a survey, and identify sources of error in survey research. The course will also establish how each aspect of a survey can affect its accuracy and credibility, and confront the practical problems of survey research, exploring the theoretical and methodological issues at stake. (2 credits)