In-Depth Notes on Sampling in Auditing

Chapter 8 - Sampling

Definition of Sampling

  • Sampling: Application of an audit procedure to less than 100% of items within an account balance or class of transactions to evaluate characteristics of that balance or class.
  • Source: AS 15, par. 28

Benefits and Risks of Sampling

  • Benefits: Cost-effective, time-efficient, allows auditors to draw conclusions without examining entire populations.
  • Risks: Inaccuracies due to sampling risk and nonsampling risk.

Types of Risk

  • Sampling Risk: The possibility that the sample drawn is not representative of the population, potentially leading to incorrect conclusions.
  • Incorrect Rejection (Type 1): Concludes control is not effective when it is.
  • Incorrect Acceptance (Type 2): Concludes control is effective when it is not.
  • Nonsampling Risk: Arises from human judgment errors, such as inappropriate procedures or incorrect interpretations.

Audit Efficiency vs. Effectiveness

  • Efficiency: Related to reducing time and resources spent in audits.
  • Effectiveness: Concerned with obtaining accurate and reliable results.

When to Use Statistical Sampling

  • Ideal when:
  • Exact information isn’t required.
  • Population is large and homogeneous.
  • Trade-offs between effectiveness and efficiency.

Determining Test Objectives

  • Tests of Controls: Validity of controls in place.
  • Binary Outcome: Control is either working or not.
  • Substantive Tests: Assess the reasonableness of assertions.
  • Focus on material correctness of valuations.

Defining the Population

  • Key considerations include:
  • Assertion tested.
  • Test objectives must ensure population completeness.

Defining the Sampling Unit

  • Individual elements of the population.
  • Tests of Controls Examples: Individual invoices or items on an invoice.
  • Substantive Tests Examples: Customer balances or specific invoices.

Determining the Sampling Technique

  • Statistical Techniques: Equal probability and monetary unit sampling.
  • Non-Statistical Techniques: Haphazard, block selection, judgmental selection.

Sample Size Determinants

  • Sample size influenced by:
  • Tolerable Deviation Rate: Higher tolerance means smaller sample sizes.
  • Expected Population Deviation Rate: Higher expectations necessitate larger sample sizes.
  • Desired Confidence Level: Higher confidence levels require larger samples.

Factor Effects on Sample Size

  • Population size has minimal effect unless small (less than 1,000 items).
  • Expected deviation rate directly affects sample size.
  • Tolerable deviation rate inversely relates to sample size.
  • Desired confidence level directly influences sample size.

Sampling Risk Example

  • Example with 100 pens (red or blue).
  • To test percentage of red pens, options include counting all or random sampling.

Tests of Controls and Sampling Deviations

  • When sample deviation rate is low compared to tolerable deviation rate, concerns arise over either Type 1 or Type 2 errors depending on context.

Understanding and Analyzing Deviations Observed

  • Qualitative aspects matter:
  • Determine the nature (error or fraud) and its consequences (monetary misstatement).

Documenting the Sampling Procedure

  • Important documentation includes:
  • Materiality threshold (tolerable misstatement).
  • Summary of accumulated misstatements.
  • Auditor’s conclusions and rationale for decisions made.