Catalogue

Description

Part 1: Audit sampling – Introduction to basic sampling concepts and terms

This course will be an overview of:

• When audit sampling is valuable.
• Audit sampling and audit evidence.
• Sampling risk in statistical and non-statistical sampling.
• The steps used to perform an audit sampling application.
• The audit risk model. Basic terms and concepts in sampling.

After completing this course, the learner should be able to:

• Recognize the audit risk model and how it can be used with sampling to accomplish audit objectives.
• Identify the basic terms and concepts we will be using in the course that are common to all samples.
• Distinguish between statistical and non-statistical methods when sampling is performed.
• Recognize some basic situations when sampling is being applied.

Part 2: Audit sampling – Attribute sampling for tests of controls and selecting a representative sample

This course will be an overview of:

• Attribute sampling and audit sampling.
• Sample size determination.
• Sample selection.
• Issues relating to tests of controls.
• Performing audit procedures.
• Evaluating sampling results and documentation.

After completing this course, the learner should be able to:

• Recognize how attribute sampling can meet stated audit objectives.
• Determine defensible attribute sample sizes and evaluate sample results.
• Identify common attribute sampling issues and some practical solutions.
• Recognize issues that can arise when selecting a sample and simple solutions to some of these problems.
• Identify basic concepts of non-statistical sampling.

Part 3: Audit sampling – Substantive audit sampling | An introduction

This course will be an overview of:

• Determining the extent of further audit procedures.
• Substantive audit sampling techniques and tolerable misstatement.
• Audit implications of substantive test results.
• Communications with management and governance.
• Techniques for substantive detail test sampling.
• Monetary unit sampling Selecting a PPS sample.
• Differentiate MUS from other sampling methods.

After completing this course, the learner should be able to:

• Recognize the relationship of substantive detail sampling to the risk of material misstatement (RMM) and other substantive audit procedures.
• Recognize the audit implications of factual (known) misstatements identified in sampling and non-sampling procedures.
• Recognize the audit implications of projected misstatements from sampling procedures.
  Recognize how to select a valid item-based or probability proportional to size (PPS)-based statistical sample.

Part 4: Audit sampling – Classical variables sampling (CVS) techniques

This course will be an overview of:

• Classical Statistical Sampling.
• Applying CVS Sampling.
• Theory of Classical Statistical Sampling.
• The Audit Application of This Theory.
• Process of CVS Statistical Sampling.
• Implementation of a Classical Statistical Sample.
• Variables Sampling Schematic for Substantive Sampling.
• Emulating CVS Using Non-statistical Methods.

After completing this course, the learner should be able to:

• Recognize basic concepts of classical variables sampling (CVS).
• Recognize how software can be used when CVS sampling is planned and performed.
• Recognize some of the practical issues that can arise when CVS is applied in an audit context.