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Audit Testing & Sampling Methodology
This episode of the ISACA Certified Information Systems Auditor (CISA) exam prep series covers the testing and sampling techniques that allow auditors to draw sound conclusions without inspecting every item in a population. It distinguishes compliance testing from substantive testing, explains when to use statistical versus judgmental sampling, and introduces the key sampling models and risk concepts that frequently appear in CISA questions.
What this episode covers
- Compliance vs. substantive testing — what each type is designed to confirm and how the strength of controls determines how much substantive work is needed.
- Statistical sampling — how probability mathematics produces quantifiable conclusions when every item has an equal chance of selection.
- Judgmental sampling — using professional judgment to select the most material and risky items when a population-wide conclusion is not needed.
- Key sampling terms — confidence coefficient, level of risk, precision, expected error rate, sample mean, standard deviation, and tolerable error rate.
- Attribute sampling models — plain attribute, stop-or-go, and discovery sampling, each suited to different compliance testing scenarios.
- Variable sampling models — stratified mean per unit, unstratified mean per unit, and difference estimation for substantive monetary testing.
- Sampling risk — the two directions of error (incorrect acceptance and incorrect rejection) and why sample design matters so much.
Watch the full episode above for the worked examples and detailed explanations of each concept.
Frequently Asked Questions
What is the difference between compliance testing and substantive testing?
Compliance testing evaluates whether controls are operating effectively by checking whether they follow management policies — for example, sampling program versions to confirm a library control exists and works. Substantive testing confirms the integrity of actual transactions and data, verifying the validity of balances and the accuracy of processing such as interest calculations or report completeness.
How do statistical and judgmental sampling differ?
Statistical sampling uses the mathematics of probability to calculate sample size, select items, and evaluate results in a mathematically quantifiable way — every item in the population must have an equal chance of selection. Judgmental (nonstatistical) sampling relies on the auditor’s judgment to set the method, size, and selection of items that appear most material and most risky.
What are attribute sampling and variable sampling used for?
Attribute sampling is used mainly in compliance testing; it deals with whether a specific attribute is present or absent and answers the question of how many items have a characteristic. Variable sampling is used mainly in substantive testing; it estimates a monetary value or other measurable amount and tells the auditor about deviations from the norm.
What are the two types of sampling risk an auditor faces?
The first is the risk of incorrect acceptance — judging a weakness unlikely when the population is actually misstated, which could lead to signing off on a flawed control environment. The second is the risk of incorrect rejection — judging a weakness likely when the population is actually fine, which wastes audit effort and may cause unnecessary concern.
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Reference: This article is based on concepts discussed in Audit Testing & Sampling Methodology.