Applying the Federal Tax Guidance to Statistics: What It Means in Practice

Overview

Join Ryan and the Statistical Auditing Interest Group (SAIG) of the American Statistical Association (ASA) for an interactive virtual roundtable exploring the continued and central role of statistical sampling in tax audits and federal tax applications.

This exclusive webinar brings together tax sampling practitioners, statisticians, audit professionals, and industry experts to discuss how statistical methodologies have become generally accepted audit techniques in the tax profession and how these methodologies can be applied to improve tax compliance, increase audit efficiency, and enhance tax reviews, including federal research and development projects.

Through a practical panel discussion, attendees will gain insights into current challenges, emerging trends, and proven approaches for applying statistical sampling in complex tax environments. Whether you work in tax controversy, audit defense, compliance, R&D tax credits, or statistical analysis, you’ll leave with valuable perspectives and actionable takeaways.

Key Learning Objectives

• Optimize tax audit sampling using proven methodologies and best practices

• Understand the role of statistical sampling in federal tax and compliance initiatives

• Identify and mitigate common sampling risks in audit and R&D environments

• Stay informed on emerging developments in tax, analytics, and regulatory oversight
  

Hear from leading tax, audit, and statistical experts as they share real-world experiences and practical guidance. Attendees will have the opportunity to earn Continuing Professional Education (CPE) credit, participate in a live Q&A, and connect with peers across the tax, audit, and statistical communities.

Reserve your place today and join the conversation shaping the future of tax audit sampling. Live webinar participants may be eligible for up to 1.2 CPE credits.

Can’t attend live? Register to receive access to the on-demand recording and watch at your convenience.