Study guide
21.1 Audit Sampling Risk and Sample Design
Uniform CPA Examination Exam
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1 Chapter 1: CPA Exam Structure and Licensure Rules
1.1 CPA Evolution Model 1.2 Eligibility, Credit Window, and Scheduling Rules 1.3 Scoring, Pass Rates, and Blueprints
2 Chapter 2: CPA Scoring, Interface, and Exam Strategy
Score Scale and Testlets MCQ/TBS Weighting by Section Sample Test Interface Tools Exam-Day Time Management
3 Chapter 3: AUD Ethics, Independence, and Engagement Acceptance
3.1 Professional Responsibilities and Independence 3.2 Engagement Acceptance and Continuance 3.3 Audit Documentation and Quality Management 3.4 Audit Risk Foundations
4 Chapter 4: AUD Risk Assessment, Controls, and Evidence
4.1 Assertions and Risk Assessment 4.2 Internal Control Design and Operating Effectiveness 4.3 Substantive Procedures and Audit Evidence 4.4 Sampling, Analytics, and Estimates
5 Chapter 21: AUD Sampling, Analytics, and Accounting Estimates
21.1 Audit Sampling Risk and Sample Design 21.2 Substantive Analytical Procedures 21.3 Estimates, Fair Value, and Specialists 21.4 Data Analytics, Exceptions, and Follow-Up
6 Chapter 22: AUD Integrated Audits, IT Controls, and SOC Reliance
22.1 ICFR Integrated Audit Framework 22.2 IT General Controls and Application Controls 22.3 Service Organizations, SOC Reports, and CUECs 22.4 Control Deficiencies and Material Weaknesses
7 Chapter 5: AUD Reporting, Attestation, and Review Engagements
5.1 Audit Opinions and Modifications 5.2 Emphasis, Other Matter, and Going Concern 5.3 Review, Compilation, and Preparation Engagements 5.4 Attestation and Government Auditing Signals
8 Chapter 36: AUD Workbook - From Risk to Report
36.1 Risk-Assertion-Procedure Drill 36.2 Evidence Reliability Drill 36.3 Control Deficiency Classification Drill 36.4 Report Modification Decision Drill
9 Chapter 6: FAR Financial Statements and Reporting Framework
6.1 Conceptual Framework and Standard Setting 6.2 Financial Statement Presentation 6.3 Cash Flow Statement and Disclosures 6.4 Not-for-Profit Reporting Basics
10 Chapter 7: FAR Balance Sheet Accounts and Rollforwards
7.1 Cash, Receivables, and Reconciliations 7.2 Inventory and Cost Flow Errors 7.3 Property, Equipment, and Intangibles 7.4 Debt, Equity, and Contingencies
11 Chapter 8: FAR Selected Transactions and Measurement Models
8.1 Revenue Recognition: Five-Step Model 8.2 Leases, Income Taxes, and Impairment 8.3 Business Combinations and Consolidations 8.4 Accounting Changes, Errors, and Subsequent Events
12 Chapter 32: FAR Revenue, Leases, and Income Taxes Deep Dive
32.1 Revenue Contract Modifications and Variable Consideration 32.2 Lease Classification and Lessee Accounting 32.3 Deferred Tax Assets, Liabilities, and Valuation Allowances 32.4 Simulation Workflows for Revenue, Lease, and Tax Exhibits
13 Chapter 31: FAR Financial Instruments, Fair Value, and Derivatives
31.1 Financial Asset Classification and Measurement 31.2 Fair Value Hierarchy and Disclosures 31.3 Derivatives, Hedge Accounting, and Embedded Features 31.4 Foreign Currency and Comprehensive Income Signals
14 Chapter 24: FAR Consolidations, Equity Method, and Intercompany Workpapers
24.1 Consolidation Decision and Noncontrolling Interest 24.2 Acquisition-Date Measurement and Goodwill 24.3 Equity Method Income, Dividends, and Impairment 24.4 Intercompany Inventory, Debt, and Fixed Asset Eliminations
15 Chapter 9: FAR Governmental Accounting and Fund Reporting
9.1 Governmental Fund Types and Basis 9.2 Government-Wide Statements and Reconciliations 9.3 Budgetary Accounting and Encumbrances 9.4 Governmental and NFP Comparison Traps
16 Chapter 23: FAR Not-for-Profit and Special Reporting Topics
23.1 Not-for-Profit Net Assets and Restrictions 23.2 Contributions, Conditional Gifts, and Agency Transactions 23.3 Functional Expenses and Statement Presentation 23.4 Interim, Segment, and EPS Reporting Traps
17 Chapter 37: FAR Workbook - Journal Entries, Rollforwards, and Reconciliations
Adjusting Entry Workflow Account Rollforward Workflow Reconciliation and Error Correction Drill Statement Presentation Workpaper Drill
18 Chapter 10: REG Tax Procedure, Ethics, and Business Law
10.1 Tax Practice Ethics and Preparer Responsibilities 10.2 IRS Procedure, Statutes, and Penalties 10.3 Contracts, Agency, and Business Entities 10.4 Secured Transactions, Bankruptcy, and Priority
19 Chapter 11: REG Individual Federal Tax Workflows
11.1 Gross Income, Exclusions, and Adjustments 11.2 Filing Status, Dependents, and Deductions 11.3 Credits, Payments, and AMT Concepts 11.4 Retirement, Passive Activity, and Loss Limitations
20 Chapter 12: REG Property Transactions and Entity Taxation
12.1 Basis, Realized Gain, Recognized Gain, and Character 12.2 C Corporations and Shareholder Transactions 12.3 S Corporations, Partnerships, and Basis 12.4 Entity Tax Simulations and K-1 Workflows
21 Chapter 25: REG Entity Choice, Basis, and Owner Tax Consequences
25.1 C Corporation, S Corporation, and Partnership Comparison 25.2 Formation Contributions and Built-In Gain 25.3 Distributions, Redemptions, and Liquidations 25.4 Loss Limits: Basis, At-Risk, and Passive Rules
22 Chapter 26: REG Property Tax, Character, and Deferral Transactions
26.1 Capital, Ordinary, and Section 1231 Character 26.2 Depreciation Recapture and Unrecaptured Gain 26.3 Like-Kind Exchanges, Involuntary Conversions, and Installment Sales 26.4 Related-Party, Wash-Sale, and Imputed-Interest Traps
23 Chapter 33: REG Trusts, Estates, Gifts, and Exempt Organizations
33.1 Trust and Estate Income Tax Basics 33.2 Gift, Estate, and Beneficiary Planning Concepts 33.3 Tax-Exempt Organizations and Unrelated Business Income 33.4 Fiduciary K-1 and Distribution Simulation Workflows
24 Chapter 38: REG Workbook - Tax Return Schedules and Basis Workpapers
38.1 Individual Return Classification Drill 38.2 Property Basis and Character Workpaper 38.3 Pass-through K-1 and Owner Basis Workpaper 38.4 Business Law Issue Spotting Drill
25 Chapter 13: BAR Business Analysis, Economics, and Forecasting
13.1 Financial Statement Analysis and Ratios 13.2 Variance, Forecasting, and Budgeting 13.3 Cost Accounting and Performance Management 13.4 Economics, Finance, and Decision Models
26 Chapter 14: BAR Technical Accounting and Advanced Reporting
14.1 Revenue, Leases, and Complex Arrangements 14.2 Derivatives, Hedges, and Fair Value 14.3 Business Combinations and Consolidations 14.4 SEC Reporting and Public Company Context
27 Chapter 15: BAR State and Local Government Analysis
15.1 Governmental Fund Analysis 15.2 Government-Wide Conversion Workflows 15.3 Budgetary Reconciliation and CAFR/ACFR Reading 15.4 Government Simulation Strategy
28 Chapter 16: ISC Information Systems and Data Management
16.1 Systems Architecture and Data Flow 16.2 ERP, Accounting Systems, and Change Management 16.3 Data Governance, SQL, and Analytics 16.4 Availability, Backup, and Recovery Controls
29 Chapter 17: ISC Security, Privacy, and SOC Engagements
17.1 Security Threats and Control Selection 17.2 Privacy, Confidentiality, and Compliance Frameworks 17.3 SOC 1, SOC 2, SOC 3, and Cybersecurity Reports 17.4 Service Organization Exceptions and User Controls
30 Chapter 18: TCP Individual Tax Planning and Personal Financial Issues
18.1 Nonroutine Individual Income and Estimated Tax 18.2 Passive, At-Risk, and Investment Planning 18.3 Retirement, Education, and Insurance Planning 18.4 Gift, Estate, and Beneficiary Concepts
31 Chapter 19: TCP Entity Compliance and Planning
19.1 C Corporation Tax Planning 19.2 S Corporation Basis and Distributions 19.3 Partnership Tax Planning and Allocations 19.4 Trusts, Tax-Exempt, and International Signals
32 Chapter 34: TCP International and Advanced Entity Tax Topics
34.1 International Tax Signals and Source of Income 34.2 CFC, Foreign Tax Credit, and Permanent Establishment Concepts 34.3 Consolidated Returns and Affiliated Corporations 34.4 Advanced Partnership and S Corp Planning Scenarios
33 Chapter 35: Choosing and Preparing for BAR, ISC, or TCP
35.1 Discipline Fit Matrix by Background 35.2 BAR, ISC, and TCP Blueprint and Skill Comparison 35.3 Discipline Study Plans and Practice Balance 35.4 Switching Disciplines, Retake, and Score Interpretation
34 Chapter 39: CPA TBS Research, Authoritative Literature, and Document Review
39.1 Document Review Simulation Method 39.2 Research and Authoritative Literature Workflow 39.3 Exhibit Overload and Relevant Data Selection 39.4 Written Explanation and Professional Judgment Drills
35 Chapter 20: CPA Simulations, Retakes, and Final Review
20.1 TBS Exhibit Triage and Workpaper Method 20.2 Section-Specific Final Review Plans 20.3 Score Release, Retake, and Credit Window Decisions 20.4 Four-Section Study Roadmaps
36 Chapter 40: Discipline Workbook Drills for BAR, ISC, and TCP
40.1 BAR Ratio, Variance, and Government Drill 40.2 ISC Control Evidence and SOC Drill 40.3 TCP Basis Planning and Entity Drill 40.4 Discipline Final Mock and Review Log
21.1 Audit Sampling Risk and Sample Design
Key Takeaways Explain This Topic AI
Sampling lives in AUD Area III, Performing Further Procedures and Obtaining Evidence, weighted 30-40% of a section graded 50% MCQ and 50% task-based simulation.
Sampling risk is the risk that a conclusion from a sample differs from the conclusion testing the entire population would produce; non-sampling risk comes from auditor error, not sample size.
A valid sample requires a population that matches the assertion: occurrence of sales uses recorded entries, while completeness of liabilities uses unmatched receiving reports and subsequent disbursements.
Sample size rises as tolerable misstatement falls, expected misstatement rises, or the auditor demands a lower risk of incorrect acceptance.
Projected misstatement plus known misstatement plus an allowance for sampling risk must be compared to tolerable misstatement before the auditor concludes.
Last updated: June 2026
Where Sampling Sits on the 2026 AUD Exam
The 2026 Auditing and Attestation (AUD) section is four hours long, contains 78 multiple-choice questions and 7 task-based simulations, and is scored 50% on each format with a passing scaled score of 75. Audit sampling falls in Area III, Performing Further Procedures and Obtaining Evidence, weighted 30-40%, the heaviest area on the exam. Expect both MCQs that test direction-of-change reasoning and simulations that hand you a population, a tolerable misstatement, and sample results to evaluate.
Audit sampling , governed by AU-C 530, is the application of an audit procedure to less than 100% of a population so that the auditor can draw a conclusion about the whole population. It is used in tests of controls and substantive tests of details. It is not the same as haphazardly inspecting a handful of invoices. A defensible sample has a defined objective, a complete and relevant population, an unbiased selection method, and a conclusion that accounts for sampling risk.
Sampling Risk vs. Non-Sampling Risk
Sampling risk is the risk that the sample supports a conclusion different from the one testing the entire population would support. It has two aspect pairs the exam loves:
Tests of controls: risk of overreliance (assessing control risk too low, the dangerous one because it impairs audit effectiveness) vs. risk of underreliance (assessing too high, which hurts efficiency).
Substantive tests: risk of incorrect acceptance (concluding a materially misstated balance is fair, the effectiveness risk) vs. risk of incorrect rejection (the efficiency risk).
Non-sampling risk is unrelated to sample size. It arises from using the wrong procedure, misreading evidence, failing to recognize an exception, or drawing a poor conclusion from correct data. A larger sample lowers sampling risk but never cures a bad population or an irrelevant procedure. The CPA trap: candidates pick "increase the sample" when the real defect is a population that does not address the assertion.
Design Choices and the Population Trap
Design choice Test of controls Substantive detail
Objective Is the control operating effectively? Is the balance or class misstated?
- Population Items subject to the control Recorded or omitted items tied to an assertion
- "Exception" means Deviation from the prescribed control Monetary misstatement or unsupported item
- Tolerable level Tolerable deviation rate Tolerable misstatement
- Output Deviation rate, control-risk decision Projected misstatement, balance conclusion
Population design is the most common sampling trap. To test occurrence of recorded sales, the population is recorded sales entries (vouch from the ledger to shipping documents). To test completeness of liabilities, the recorded payable ledger is the wrong population, because it cannot reveal what was omitted. Instead, sample unmatched receiving reports, subsequent-period cash disbursements, open purchase orders, and vendor statements, then trace them into the recorded payables. Direction of testing follows the assertion.
What Moves Sample Size
Sample size increases when the auditor wants lower sampling risk, expects more exceptions, or sets a lower tolerable rate or tolerable misstatement. It decreases when acceptable risk is higher, expected exceptions are lower, or the population is stratified so high-value items are isolated.
- Factor Change Effect on sample size
- Tolerable misstatement Decrease Increase
- Expected misstatement Increase Increase
- Acceptable risk of incorrect acceptance Decrease Increase
- Population variability (standard deviation) Increase Increase
- Population size (large populations) Increase Negligible effect
Stratification splits a population into groups with similar characteristics. For accounts receivable, the auditor might examine 100% of individually significant balances, separately sample old past-due accounts, and sample small current balances at a lower rate. Monetary-unit sampling (MUS) , a probability-proportional-to-size method, automatically gives larger balances a higher chance of selection, making it efficient for testing overstatement in receivables and inventory.
Evaluation Workflow
State the objective and assertion.
Define the population; verify it is complete and relevant for that objective.
Choose a selection method: random, systematic (with a random start), monetary-unit, or unbiased haphazard.
Perform the procedure and identify exceptions precisely.
Project sample results to the population (e.g., a $40,000 misstatement in a $400,000 sample drawn from a $4,000,000 stratum projects to roughly $400,000).
Compare projected misstatement + known misstatement + an allowance for sampling risk against tolerable misstatement.
Decide on additional procedures, an adjustment, or a revised risk assessment.
The best AUD answer protects the conclusion. If exceptions exceed expectations, the auditor does not dismiss them because the sample was small. The auditor investigates the nature and cause of each exception, considers whether it signals a control deficiency or a systematic misstatement, revises risk if warranted, and extends procedures when the evidence no longer supports the original plan. A single deviation that reveals a fraudulent override is qualitatively significant even if the quantitative rate looks acceptable.
Attribute Sampling for Tests of Controls
For tests of controls the auditor usually uses attribute sampling and computes a deviation rate. Suppose the tolerable deviation rate is 7%, the expected population deviation rate is 1.5%, and the desired risk of overreliance is 5%. A sample table yields, say, 50 items; finding two deviations gives a sample deviation rate of 4% and, after adding an allowance for sampling risk, an upper deviation rate that the auditor compares to the 7% tolerable rate. If the upper deviation rate is at or below the tolerable rate, the auditor may rely on the control as planned.
If it exceeds the tolerable rate, the auditor lowers reliance, increases substantive testing, and considers whether a control deficiency exists. The exam rewards candidates who keep tolerable deviation rate separate from tolerable misstatement: deviation rates apply to controls, dollar misstatements apply to substantive tests.