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Graduate School USA

Practical Statistical Sampling for Auditors Course

via Graduate School USA

Overview

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.

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

Reviews

4.7 rating at Graduate School USA based on 3 ratings

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