Audit Sampling Training Course

Duration 10 days 20 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends External Auditors, Internal Auditors and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-A-135

Before you join: Participants should understand the purpose of an audit, the difference between tests of controls and substantive procedures, and common financial statement assertions.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Audit sampling determines whether audit conclusions are supported by sufficient appropriate evidence without testing every transaction or balance. Poorly designed samples can omit high-risk items, produce biased selections, misstate the projected error, or leave reviewers unable to reconstruct the auditor’s reasoning. This course addresses the judgement, documentation and quantitative methods needed to select, test and evaluate samples for controls testing and substantive procedures.

Participants work through attribute sampling, variables sampling, monetary-unit sampling, non-statistical sampling and targeted selection. They learn to define the population and sampling unit, assess completeness, set tolerable misstatement or tolerable deviation rates, determine sample sizes, select items, investigate exceptions and project misstatements. The course applies ISA 530 requirements alongside ISA 500 evidence principles and ISA 450 evaluation of misstatements. Cases cover revenue, payroll, procurement, inventory, loan portfolios and grant expenditure.

Teaching combines concise technical briefings, worked calculations, instructor-led case analysis, group review of audit evidence and individual workpaper preparation. Participants progressively build an audit sampling file using planning schedules, selection documentation, testing records, exception analyses and conclusion memoranda. They leave with a completed sampling workpaper pack that can be adapted for their audit methodology, subject to firm policies and applicable auditing standards.

The course suits auditors and assurance professionals who already perform audit testing and need greater confidence in designing and defending samples. It is relevant to external audit, internal audit, public-sector assurance, compliance testing and grant assurance assignments.

What you will be able to do

  • Design risk-based audit samples using ISA 530 requirements and audit objectives
  • Define complete populations, sampling units, strata and high-value selections
  • Calculate statistical sample sizes for attribute and variables testing
  • Apply monetary-unit sampling to substantive testing of account balances
  • Select sample items using random, systematic and haphazard selection methods
  • Evaluate deviations, misstatements and projected errors against tolerable thresholds
  • Document sampling rationale, testing results and audit conclusions in workpapers
  • Present a completed audit sampling plan and conclusion memorandum

Benefits of attending

For you

  • Greater confidence defending sample rationale during manager and partner review
  • Practical ability to calculate and document statistically valid sample sizes
  • Clearer judgement when evaluating control deviations and financial misstatements
  • Reusable workpapers for substantive and controls testing assignments
  • Stronger readiness for audit senior and assurance manager responsibilities

For your organisation

  • More consistent audit sampling methods across teams and engagements
  • Better documented evidence supporting audit opinions and assurance conclusions
  • Reduced rework caused by incomplete populations or unsupported sample sizes
  • Earlier identification of control failures and material misstatement risks
  • Improved quality review outcomes for sampling workpapers and conclusions

Course modules

20 modules over 10 days

Participants can explain when sampling provides sufficient appropriate audit evidence.

  • Audit objectives, assertions and evidence requirements driving sampling decisions
  • ISA 530 requirements for designing, selecting and evaluating audit samples
  • ISA 500 evidence principles affecting reliability of sampled audit evidence
  • Sampling risk, non-sampling risk and their different audit responses
  • Population, sampling unit and sample frame defined for audit testing
  • Tests of controls and substantive procedures distinguished through evidence objectives

Participants can translate audit risks and objectives into a documented sampling approach.

  • Financial statement assertions linked to relevant sampling objectives
  • Risk assessment results translated into planned audit testing responses
  • Materiality, performance materiality and tolerable misstatement compared
  • Tolerable deviation rate established for key control testing
  • Expected misstatement and expected deviation rate assessed from prior evidence
  • Audit strategy documented with population-specific sampling rationale

Participants can define a complete and appropriate population for audit sampling.

  • Population boundaries aligned with audit objective and reporting period
  • Completeness procedures reconcile source reports to general ledger totals
  • Duplicate records, void transactions and reversals treated within populations
  • Sampling units defined as documents, transactions, balances or monetary units
  • Data extraction fields assessed for accuracy, completeness and usability
  • Population stratification separates individually significant and routine items

Participants can design non-statistical samples without introducing selection bias.

  • Non-statistical sampling judgements documented using risk and materiality factors
  • Sample size determined from assurance needs and expected error
  • Haphazard selection applied without conscious bias or predictable patterns
  • Block selection risks identified when consecutive records share characteristics
  • Targeted testing separates high-risk items from representative sample items
  • Sample results evaluated against planned tolerable error thresholds

Participants can apply core statistical concepts to audit sample design.

  • Random selection gives each population unit a known selection chance
  • Confidence level related to acceptable sampling risk and assurance
  • Precision expresses acceptable difference between sample and population results
  • Expected error affects sample size and planned audit efficiency
  • Sampling distributions explain variation between sample and population results
  • Statistical and non-statistical approaches compared under ISA 530

Participants can select sample items using suitable, reproducible selection methods.

  • Simple random selection generated from numbered population records
  • Systematic selection uses calculated intervals and random starting points
  • Random number tables and spreadsheet functions produce auditable selections
  • Stratified selections document thresholds, strata and selection methods
  • Physical document populations sampled through controlled numbering procedures
  • Selection records preserve reproducibility for reviewer reperformance

Participants can design attribute samples to test control operating effectiveness.

  • Attributes defined as observable control actions or approval requirements
  • Control population identifies every occurrence of the control activity
  • Tolerable deviation rate reflects reliance planned on the control
  • Expected deviation rate incorporates prior-year and walkthrough evidence
  • Attribute sample size determined using confidence and deviation parameters
  • Control deviations classified as failures, anomalies or documentation exceptions

Participants can evaluate sampled deviations and revise planned control reliance.

  • Deviation rates calculated from valid tested items and exceptions
  • Nature and cause of each control deviation investigated
  • Upper deviation rate compared with tolerable deviation rate
  • Anomalous deviations assessed using corroborating audit evidence
  • Control reliance revised when sample results exceed planned thresholds
  • Compensating controls evaluated before modifying substantive audit procedures

Participants can plan variables samples for testing account balances and transactions.

  • Variables sampling estimates monetary misstatement within recorded populations
  • Classical variables sampling uses mean-per-unit and difference estimation
  • Recorded value, audited value and misstatement defined consistently
  • Population variability assessed before selecting a variables sampling method
  • Tolerable misstatement allocated to account balance testing procedures
  • Sample size responds to expected misstatement and population dispersion

Participants can apply monetary-unit sampling to detect overstatement in financial balances.

  • Monetary-unit sampling assigns selection probability according to recorded value
  • Sampling interval calculated from population value and sample size
  • Random start identifies monetary units selected through cumulative values
  • Individually significant items receive automatic selection above interval thresholds
  • Overstatement risk addressed through probability-proportional-to-size selection
  • Understatement risks assessed when monetary-unit sampling is unsuitable

Participants can perform and document substantive testing of selected sample items.

  • Vouching traces recorded transactions to external supporting documentation
  • Tracing follows source documents into accounting records for completeness
  • Confirmations, invoices and contracts assessed for evidence reliability
  • Audit differences quantified between recorded amounts and audited amounts
  • Unavailable documents treated as scope limitations or alternative procedures
  • Testing sheets record procedures, evidence references and reviewer conclusions

Participants can project sample misstatements to the population using appropriate methods.

  • Factual misstatements separated from judgemental and projected misstatements
  • Ratio projection applies sample error rates to recorded population values
  • Difference projection estimates total misstatement from average sample differences
  • Monetary-unit sampling projects tainting percentages to sampling intervals
  • Stratum-specific projections combined with individually tested item misstatements
  • Projection methods selected consistently with the original sample design

Participants can evaluate projected errors against materiality and form a sampling conclusion.

  • Projected misstatement compared with tolerable misstatement and remaining audit risk
  • ISA 450 requirements applied to accumulation and evaluation of misstatements
  • Sampling risk allowance incorporated into substantive testing conclusions
  • Management explanations challenged using corroborating evidence and root-cause analysis
  • Additional testing planned when projected errors exceed acceptable thresholds
  • Uncorrected misstatements communicated for financial statement evaluation

Participants can design samples for revenue recognition and receivables audit procedures.

  • Revenue populations stratified by value, channel, period-end and contract type
  • Cut-off testing samples dispatch records, invoices and credit notes
  • Contract terms tested against revenue recognition performance obligations
  • Receivables confirmations selected using balance value and risk indicators
  • Subsequent cash receipts provide alternative evidence for receivable existence
  • Credit notes after year-end assessed for revenue reversal indicators

Participants can apply sampling methods to expenditure, payroll and approval controls.

  • Purchase-to-pay populations reconcile purchase orders, invoices and payment runs
  • Three-way matching controls tested through sampled procurement transactions
  • Delegated authority limits examined against sampled approval evidence
  • Payroll samples test employee existence, pay rates and overtime approvals
  • Duplicate payment indicators targeted through data-assisted population analysis
  • Grant expenditure samples test eligibility, procurement and supporting records

Participants can plan sampling for physical existence, valuation and asset additions.

  • Inventory test counts select items from records and warehouse locations
  • Floor-to-sheet and sheet-to-floor testing address different assertions
  • Inventory strata isolate high-value, obsolete and slow-moving stock
  • Fixed asset additions vouched to invoices, approvals and commissioning evidence
  • Disposals sampled for derecognition, proceeds and authorisation evidence
  • Observation exceptions documented with count instructions and follow-up procedures

Participants can tailor sampling plans for operational, regulatory and compliance assurance.

  • Control objectives translated into measurable compliance attributes
  • Regulatory populations segmented by obligation, risk rating and reporting period
  • Sanctions screening alerts sampled for escalation and resolution evidence
  • Loan files sampled for credit approval and covenant monitoring controls
  • Procurement compliance samples assess tender thresholds and conflict declarations
  • Issue ratings reflect control design, operating effectiveness and exposure

Participants can prepare review-ready sampling documentation and respond to challenge.

  • Sampling workpapers link objectives, populations, parameters and conclusions
  • Population reconciliation retained with source reports and control totals
  • Selection logs identify random seeds, intervals and excluded items
  • Exception evaluation records cause, impact and additional audit procedures
  • Reviewer checkpoints test compliance with methodology and auditing standards
  • Cross-references connect sample results to audit programme conclusions

Participants can use data analysis to improve population understanding and sample design.

  • Data profiling identifies missing fields, duplicates and unusual transaction patterns
  • Benford analysis flags digit anomalies requiring targeted audit consideration
  • Ageing, trend and outlier analysis inform stratification decisions
  • Full-population tests complement rather than replace auditor sampling judgement
  • Spreadsheet filters preserve selection criteria and audit trail evidence
  • Data exceptions distinguished from confirmed control or financial reporting errors

Participants can build, review and present a complete audit sampling file for a defined audit area.

  • Audit objective, assertions and population risks documented for assigned case
  • Population reconciliation and stratification schedule supports sample frame completeness
  • Sampling method, parameters and sample size justified with evidence
  • Selection log records chosen items, high-value items and exclusions
  • Testing results, exceptions and projected misstatements compiled into workpapers
  • Conclusion memorandum presents audit response, findings and reviewer-ready rationale

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Audit sampling planning template
  2. Population completeness reconciliation checklist
  3. Attribute sampling calculation model
  4. Monetary-unit sampling selection schedule
  5. Misstatement projection and evaluation worksheet
  6. Audit sampling conclusion memorandum template

Who should attend

  • External Auditors — need defensible samples for financial statement audit evidence
  • Internal Auditors — need efficient testing plans for control assurance assignments
  • Audit Seniors — supervise sample design, testing quality and workpaper review
  • Risk and Compliance Auditors — test regulatory controls and transaction populations
  • Public Sector Auditors — assess expenditure, procurement and grant compliance evidence
  • Finance Control Professionals — prepare support for auditor sampling requests

Skills and tools covered

Audit sample designStatistical samplingMisstatement projectionControl deviation evaluationSampling workpapersAudit evidence assessment

Tools and standards

ISA 530 Audit Sampling, ISA 500 Audit Evidence, ISA 450 Evaluation of Misstatements Identified during the Audit, Monetary-unit sampling

How the course runs

Training methodology

The instructor uses short technical briefings to introduce standards, sampling logic and calculation methods. Participants analyse realistic audit populations, identify population risks, calculate sample sizes and prepare selection schedules. Group work compares alternative sampling approaches for controls and substantive testing, while instructor-led reviews examine common documentation failures. Simulations require participants to assess exceptions, project errors and reach audit conclusions. Individual application planning links the course templates to participants’ own audit programmes, sector requirements and quality review procedures.

Requirements and prerequisites

Participants should understand the purpose of an audit, the difference between tests of controls and substantive procedures, and common financial statement assertions. Experience preparing or reviewing audit working papers, performing transaction testing, or supporting auditors is useful. Participants should be comfortable with percentages, ratios and basic spreadsheet calculations. Prior statistical training is not required; probability concepts and sample-size logic are taught from first principles. No specialist audit software, programming knowledge, professional designation or prior experience with monetary-unit sampling is required.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should understand basic audit concepts, financial statement assertions and common audit testing procedures. Prior statistics training is not required, but participants should be comfortable with percentages and spreadsheet calculations.

Bring a laptop with spreadsheet software if attending in person, plus any non-confidential audit programmes or sampling workpapers you want to improve. Course cases, calculation sheets and templates are provided.

It is designed for external auditors, internal auditors, audit seniors, compliance auditors and assurance professionals who already perform or review audit testing. Finance control staff supporting audit evidence will also benefit.

General auditing courses address planning, risk assessment, controls and reporting across the audit cycle. This course concentrates on selecting, testing, evaluating and documenting audit samples, including statistical and monetary-unit methods.

You can use the planning template, sample-size model, selection schedule and conclusion memorandum on current audit assignments. The methods apply to controls testing, transaction testing and substantive balance testing, subject to your firm methodology.

The first week establishes sampling standards, population definition, selection methods and controls testing. The second week covers substantive sampling, misstatement evaluation, sector cases, documentation, data analysis and the final sampling-file capstone.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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