OPIM 6203 – Seminar in Management Information Systems (PhD Level)

OPIM 6203 will focus on the following objectives: (1) understanding extant empirical methodologies widely used in information systems, economics, marketing, and other disciplines. (2) developing skills for critically analyzing recent empirical research papers (including causal inference based on observational studies and randomized experiments). (3) learning the application of machine learning (ML) in business research and acquainting with the latest advancements in AI/ML.

OPIM 5603 – Statistics in Business Analytics (Graduate Level)

OPIM 5603 introduces you to the concepts of population and sample; the difference between population parameters and sample statistics, and how to draw an inference from known sample statistics to usually unknown population parameters. Topics include: descriptive and inferential statistics, data visualization, discrete and continuous random variables, sampling, probability, confidence intervals, hypothesis testing, linear regression, and logistic regression.

Objectives: 1) Conceptually understand key topics in statistical inference (e.g., sampling, probability, confidence intervals); 2) Practical application of R for data analysis and visualization, statistical hypothesis tests, and regressions.

OPIM 3103 – Business Information Systems (Undergraduate Level)

OPIM 3103 introduces you to Management of Information Systems (MIS) concepts, tools, and techniques used in various functions of a business enterprise. It covers both Microsoft Excel spreadsheets and Microsoft Access database.

Objectives: 1) Introduction to Microsoft Excel and the design of spreadsheets to enable efficient decision making in business situations, through hands-on learning activities; 2) Introduction to Microsoft Access and the design of databases to enable efficient data management and reporting in business situations, again through hands-on learning activities.