Audit Sample Size Calculator

Classical Sampling Method (Representative Sampling)

This template documents sample size calculation using classical sampling method for OSP (Overall Sampling Procedure) in accordance with International Auditing Standards.

Client & Engagement Information

Client Name

Engagement Code

Financial Statement Area Select area... Revenue Expenses Assets Liabilities Equity

Population Parameters

First Voucher Number

Starting serial number of the population

Last Voucher Number

Ending serial number of the population

Population Size (Number of Items)

Calculated as: (Last Voucher - First Voucher) + 1

Account Balance

$

Materiality & Exclusions

Performance Materiality

$

Tolerable misstatement for this audit area

Key Items Value (100% Testing)

$

High-value items tested 100% (excluded from sampling)

Other Excluded Items Value

$

Items excluded for specific reasons (e.g., negative balances)

Sampling Base

Account Balance - (Key Items + Other Exclusions)

Assurance Considerations & Factors

Consideration	Assessment	Impact Factor
IRAM Level i Inherent Risk Assessment at the Assertion Level Higher inherent risk requires more audit evidence. Significant risk = 3.0, Moderate = 2.0, Low = 1.0	Significant (3.0) Moderate (2.0) Low (1.0)	3.00
Assurance from Tests of Controls (TOCs) i Reliance on Internal Controls Effectiveness of controls reduces substantive testing. None = 0, Low = 0.5, Moderate = 1.0, Significant = 2.0	None (0.0) Low (0.5) Moderate (1.0) Significant (2.0)	0.00
Assurance from Substantive Analytical Procedures (SAPs) i Analytical Procedures Evidence Reliance on analytical procedures reduces detailed testing. None = 0, Low = 0.5, Moderate = 1.0, Significant = 2.0	None (0.0) Low (0.5) Moderate (1.0) Significant (2.0)	0.00
Assurance from Other OSPs i Other Overall Sampling Procedures Evidence from related audit procedures. None = 0, Low = 0.5, Moderate = 1.0, Significant = 2.0	None (0.0) Low (0.5) Moderate (1.0) Significant (2.0)	0.00
Assurance from Data Analytics (DA) i Data Analytics Procedures Audit evidence obtained through data analytics tools. None = 0, Low = 0.5, Moderate = 1.0, Significant = 2.0	None (0.0) Low (0.5) Moderate (1.0) Significant (2.0)	0.00
Total Assurance Factor:		3.00

Sampling Parameters

Population Variability Consideration Stratification or MUS/CVS used (Multiplier: 1.0) No stratification used (Multiplier: 1.25)

Accounting populations with high variability require larger samples

Confidence Level High (Substantive testing) Moderate Low (Tests of controls)

Sample Size Calculation Results

Initial Sample Size

-

Based on sampling base and materiality

Variability Adjusted Size

-

After applying variability multiplier

Key Items (100% Tested)

0

High-value items tested separately

Total Sample Items

-

Including key items and sampling items

Sampling Interval

-

Population Size ÷ Total Sample Items (rounded)

Selection Methodology

Systematic Selection

Every nth item after random start

Calculation Methodology

Sampling Base = Account Balance - (Key Items + Other Exclusions)

Initial Sample Size = (Sampling Base ÷ Performance Materiality) × Total Assurance Factor

Adjusted Sample Size = Initial Sample Size × Variability Multiplier × Confidence Level

Key Items Count = Based on professional judgment (typically items > materiality threshold)

Total Sample = Adjusted Sample Size + Key Items Count

Sampling Interval = Population Size ÷ Total Sample Items (rounded down)

Sample Selection Details

Parameter	Value	Description
Population Range	-	First to last voucher in population
Population Size	-	Total number of items in population
Sampling Base	-	Monetary value subject to sampling
Assurance Factor	-	Combined assurance from all sources
Variability Multiplier	-	Adjustment for population variability

Selected Sample Items

Sample No.	Voucher Number	Selection Method

Notes on Sampling Methodology

International Auditing Standards Compliance: This calculator follows ISA 530 (Audit Sampling) requirements for designing and selecting audit samples. Sample sizes are determined based on risk assessment, materiality, and expected misstatements.

Population Variability Consideration: Accounting populations typically have high variability with few large amounts and many small amounts. When stratification or Monetary Unit Sampling (MUS) is not used, sample size should be increased by 25% (multiplier 1.25) to address this variability.

Tolerable Misstatement: Performance materiality is set at an amount lower than overall materiality to reduce the probability that undetected and uncorrected misstatements exceed materiality. Tolerable misstatement for sampling purposes may be equal to or lower than performance materiality.