Applying Regression Analysis in an Auditing Context

Bridging the Gap from Theory to Practices

This is a fun, recently accepted project, undertaken with my Texas State colleagues, Ann Watkins and Billy Brewster. It’s a case/learning strategy that gently bridges the gap between theoretical statistics and practical auditing applications. It demonstrates how regression analysis, often viewed by students as an abstract concept from their business statistics courses, becomes a useful tool in the auditor’s arsenal. Students gain hands-on experience in using regression to develop expectations and identify potential misstatements in financial data.

Learning Objectives

Goals for the learning strategy include the following:

• Utilize Excel for regression analysis in an auditing context
• Interpret statistical outputs and relate them to audit evidence
• Develop data-driven expectations for financial statement variables
• Identify outliers and assess their potential significance
• Understand the strengths and limitations of regression analysis in auditing

Why It Matters

Regression analysis allows auditors to model complex relationships between financial variables, controlling for factors unrelated to the relationship of interest and providing a more objective basis for analytical procedures. This approach not only increases efficiency but also improves audit quality by allowing for more precise expectations and better identification of high-risk areas.