Topics covered include random sampling, risk control, estimation methods, and audit reporting as well as statistical sampling techniques for auditing using Excel. Ideal for auditors and analysts needing hands-on sampling skills.
Overview
Syllabus
Module 1: Sampling Standards and Data Description
- Understand AICPA audit sampling standards and terminology
- Explore descriptive statistics: mean, median, mode, standard deviation, and more
- Utilize Excel for descriptive statistics and frequency distributions
- Identify types of variables and understand their role in audit sampling
- Apply the concept of standard deviation and Z-values in audit contexts
Module 2: Introduction to Sampling
- Differentiate between when to sample and when not to
- Understand benefits and principles of probability sampling
- Learn types of sampling: simple, stratified, and cluster sampling
- Apply planning steps for audit sampling including sample unit selection and stratification
Module 3: Unrestricted Random Sampling
- Define simple random sampling and its role in auditing
- Generate random samples using Excel functions like RAND and RANDBETWEEN
- Use sampling results to calculate population estimates
- Practice with real-world audit scenarios involving random sampling
Module 4: Controlling Sampling Risk
- Understand types of sampling risk and how to mitigate them
- Compute precision, standard error, and confidence intervals
- Apply confidence statements and understand their impact on audit findings
- Determine sample size based on risk and desired precision
Module 5: Difference and Ratio Estimation
- Explore difference, ratio, and mean-per-unit estimation methods
- Learn their advantages, disadvantages, and statistical implications
- Apply regression estimation in sampling
- Solve problems involving these estimation techniques
Module 6: Attribute Sampling Methods
- Understand attribute data types and estimation methods
- Use attribute estimation and discovery sampling formulas
- Evaluate when to use discovery, estimation, or acceptance sampling
- Assess errors and implications of different attribute sampling strategies
Module 7: Practice Set
- Apply concepts from all previous modules in guided exercises
- Interpret and analyze real-world audit data
Module 8: Summary
- Review best practices and common pitfalls in audit sampling
- Use visual aids and summary documents to consolidate learning
- Learn to effectively report sampling results in audit documentation
Taught by
Mark Gebicke, Penny Popps, and Lyndon S. Remias