CA Inter Auditing & Ethics – Chapter 3 Notes (Part 2)

SA 530 – Sample Design, Sample Size & Selection of Items

1. Sampling Process (Flow)

The audit sampling process under SA 530 follows a systematic sequence:

Define Audit Objective
        ↓
Identify Population
        ↓
Design Sample
        ↓
Determine Sample Size
        ↓
Select Sample
        ↓
Perform Audit Procedures
        ↓
Evaluate Results
        ↓
Project Misstatements
        ↓
Form Audit Conclusion

2. Sample Design

Meaning

Sample Design means planning how the sample will be selected so that it achieves the objective of the audit.

According to SA 530, while designing a sample, the auditor should consider:

• Purpose of audit procedure
• Characteristics of population
• Nature of audit evidence required
• Possible deviations or misstatements
• Completeness of the population

Objectives of Sample Design

A good sample should:

✔ Represent the population

✔ Reduce sampling risk

✔ Achieve audit objective

✔ Provide sufficient appropriate audit evidence

Auditor should consider

(1) Purpose of Audit Procedure

Different objectives require different populations.

Example

(2) Nature of Audit Evidence

Auditor decides:

• What evidence is required?
• Which items should be tested?
• Which population is appropriate?

(3) Possible Deviations/Misstatements

Auditor must define:

• What constitutes a deviation?
• What constitutes a misstatement?

Only relevant deviations should affect conclusions.

Example

Customer pays before confirmation date but amount reaches later.

This is not necessarily a misstatement in receivable confirmation.

However, wrong posting between customer accounts may affect other audit areas but not total receivables.

Tests of Controls vs Tests of Details

3. Stratification

Meaning

Stratification means dividing the population into smaller homogeneous groups (called strata) having similar characteristics.

Purpose

To:

• Improve audit efficiency
• Reduce variability
• Reduce sample size
• Focus on risky items

Diagram

Population
      │
 ┌────┼────┐
 │    │    │
Stratum 1
Stratum 2
Stratum 3
      │
Sample from each
      │
Combine Results
      │
Final Conclusion

Example

Receivables

Above ₹10 lakh
₹5 lakh–₹10 lakh
₹1 lakh–₹5 lakh
Below ₹1 lakh

Auditor may:

• Check 100% of high-value balances
• Sample medium-value balances
• Small sample for low-value balances

Advantages

✔ Better representation

✔ Smaller sample

✔ Better audit efficiency

✔ More focus on material balances

Value-Weighted Selection

Instead of selecting items, auditor selects monetary units.

Large-value balances have higher probability of selection.

Example:

Receivable ₹25 lakh
Receivable ₹5,000
₹25 lakh account has much greater chance of selection.

Benefit:

✔ Greater attention on material items

✔ Smaller sample size

✔ Efficient audit

4. Sample Size

Meaning

Sample Size = Number of items selected for testing.

According to SA 530,

Sample should be sufficient to reduce sampling risk to an acceptably low level.

Golden Rule ⭐

Lower acceptable risk = Larger sample size

Formula (Concept)

Sampling Risk ↓
        ↓
Sample Size ↑
Sampling Risk ↑
        ↓
Sample Size ↓

Factors Affecting Sample Size (Tests of Controls)

(1) Reliance on Controls ↑

More reliance on internal controls

↓

Need more evidence

↓

Sample Size ↑

(2) Tolerable Deviation ↑

Higher acceptable deviation

↓

Sample Size ↓

(3) Expected Deviation ↑

More expected deviations

↓

Sample Size ↑

(4) Desired Assurance ↑

Higher confidence required

↓

Sample Size ↑

(5) Population Size ↑

Large population generally has little or negligible effect on sample size once it reaches a certain scale.

Memory Trick

R D E A P

• R → Reliance on controls ↑ → Sample ↑
• D → Tolerable Deviation ↑ → Sample ↓
• E → Expected Deviation ↑ → Sample ↑
• A → Assurance ↑ → Sample ↑
• P → Population Size → Negligible effect

Factors Affecting Sample Size (Tests of Details)

(1) Risk of Material Misstatement ↑

↓

Sample Size ↑

(2) Other Substantive Procedures ↑

↓

Sample Size ↓

(3) Desired Assurance ↑

↓

Sample Size ↑

(4) Tolerable Misstatement ↑

↓

Sample Size ↓

(5) Expected Misstatement ↑

↓

Sample Size ↑

(6) Stratification Used

↓

Sample Size ↓

(7) Population Size

Generally negligible effect for large populations.

Memory Trick

R O A T E S

• R → Risk ↑
• O → Other procedures ↑
• A → Assurance ↑
• T → Tolerable misstatement ↑
• E → Expected misstatement ↑
• S → Stratification

(Remember: R, A, E increase sample; O, T, S reduce sample.)

5. Selection of Items for Testing

SA 530 requires the auditor to select items so that every sampling unit has a chance of selection and the sample is representative of the population.

Methods of Sample Selection

There are five important methods:

Sample Selection Methods
1. Random Sampling
2. Systematic Sampling
3. Monetary Unit Sampling
4. Haphazard Sampling
5. Block Sampling

(1) Random Sampling

Meaning

Every item has an equal chance of selection.

Methods:

• Random Number Table
• Computer-generated Random Numbers

Suitable for homogeneous populations.

Advantages

✔ Scientific

✔ No bias

✔ Reliable

(2) Systematic Sampling

Meaning

Items are selected at a fixed interval.

Example:

Population = 5,000 invoices

Sample = 100 invoices

Interval = 5,000 ÷ 100 = 50

Every 50th invoice is selected.

Avoid using it where there is a pattern matching the interval, as it can bias results.

(3) Monetary Unit Sampling

Selection is based on monetary value.

Large-value items are more likely to be selected.

Useful for detecting overstatements.

(4) Haphazard Sampling

Auditor selects items without a structured technique, while trying to avoid conscious bias.

• No random number tables
• No fixed pattern
• Not appropriate for statistical sampling

(5) Block Sampling

Auditor selects a continuous block of transactions.

Example:

• First 100 purchase invoices of April
• Last 50 sales invoices of March

Limitation:

Transactions in a block often have similar characteristics, so conclusions may not represent the whole population.

Comparison of Selection Methods

CA Exam Quick Revision

Stratification

Divide population into homogeneous groups.

Value-weighted selection

Large-value items have higher chance of selection.

Sample Size Rule

Lower acceptable sampling risk = Larger sample size.

Five Selection Methods

RSMHB

• R – Random
• S – Systematic
• M – Monetary Unit
• H – Haphazard
• B – Block

One-Page Revision Sheet

SA 530 – Part 2
Sample Design
↓
Purpose
Population
Audit Evidence
Misstatement
Completeness
Stratification
↓
Divide Population
↓
Homogeneous Groups
↓
Smaller Sample
Sample Size
↓
Risk ↓ → Sample ↑
Risk ↑ → Sample ↓
Tests of Controls
R D E A P
Tests of Details
R O A T E S
Selection Methods
↓
Random
Systematic
Monetary Unit
Haphazard
Block
Mnemonic:
RSMHB

This completes Part 2 covering Sample Design, Stratification, Sample Size, and Selection Methods under SA 530.