Da Gong

Lecturer of Data Analytics
South Hall 223C
585-245-5260
dgong@geneseo.edu

Personal Website: https://dadasmash.github.io/dagong.github.io// I am a Lecturer of Data Analytics in the School of Business at the State University of New York, Geneseo. I received a Ph.D. in Economics from University of California, Riverside, and a M.A. in History from Graduate School of Chinese Academy of Social Sciences. My research interests are Political Economy, Development Economics, Public Economics, Culture and Institution and Applied Machine Learning. My work focus on how people’s values, beliefs, and social norms are influenced by the state. Before I graduated from UC Riverside, I served as the Lead Consultant at Graduate Quantitative Methods Center (GradQuant, UCR) from January 2023 to June 2024.

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Classes

  • DANL 101: Introduction to Data Analytics

    This course provides an applied overview of the data analytic process and methods. The goal of this course is to help students unlock the potential of data analysis and improve the ability to transform data into a powerful tool in decision making. Students will develop foundational data analytics skills to prepare for a career or future learning that involves more advanced topics in data analytics. Topics covered include (1) introduction to Data Analytics thinking, (2) data generating process and exploratory data analysis, (3) linear regression and model selection (4) classification and clustering. During the course, students will work hands-on with the R programming language and its associated data analysis libraries.

  • ECON 205: Business and Econ Statistics

    A survey of the basic statistical tools used in management decision-making and data analysis. Major topics include data organization and presentation, a review of probability concepts, sampling and sampling distributions, statistical estimation and hypothesis testing, and correlation and regression analysis. The course also emphasizes applications of statistical techniques, the use of computerized statistical packages and ethical issues in statistical analysis.

  • MGMT 350: Information Systems

    A study of the efficient use of information technology in achieving organizational goals. Emphasis is given to the study of computerized information systems within the context of the history, paradigms, research, and ethical issues of the field. Topics will include the evolution and globalization of information technology; database generation and communication via computers; computer-based information systems (e.g., data processing, management information, decision support, and expert systems); functional information systems within organizations (e.g., marketing, manufacturing, financial and accounting information systems); and the strategic management of information resources. Prerequisites: Junior standing. Restricted to School of Business majors. Others may seek permission from the School of Business.