3 credits
Spring 2026 Lecture Upper Division
Firms generate a tremendous amount of data through their financial reporting practices. This course develops the skills necessary to collect, clean, and analyze this data. The course covers foundational concepts on the properties of accounting data as well as practical skills for manipulating large-scale financial datasets. Students will explore methods for forecasting accounting earnings and develop an understanding of the association between accounting earnings and stock market returns. Also covered are techniques for assessing accounting quality, identifying accounting manipulation and fraud, understanding the implications of insider trading, and parsing textual (i.e., qualitative) financial disclosures. Through practical case studies and data-driven approaches, students will gain the skills necessary to critically evaluate financial information and make and communicate informed investment decisions. Suited for those pursuing careers in accounting, finance, or forensic analytics, this course applies computer programming and statistical analysis to accounting-related datasets to predict financial market outcomes.
Learning Outcomes1Identify relevant data sources to support a decision need.
2Manipulate large financial datasets to prepare for statistical analysis.
3Extract insights from financial datasets through statistical analysis.
4Communicate insights from analyses through written and verbal presentations.
Prerequisites
Restrictions
made by Purdue students.