| FS \ Assertion Level | L | M | H |
|---|---|---|---|
| L | 1.2 | 1.4 | 1.6 |
| M | 1.4 | 1.8 | 2.1 |
| H | 1.6 | 2.1 | 2.5 |
| Lambda (λ) | 1.2 | 1.4 | 1.6 | 1.8 | 2.1 | 2.5 | 3.0 |
|---|---|---|---|---|---|---|---|
| Confidence Level (%) | 69.881 | 75.340 | 79.810 | 83.470 | 87.754 | 91.792 | 95.021 |
| Z-score | 1.2 | 1.4 | 1.6 | 1.8 | 2.1 | 2.5 | 3.0 |
|---|---|---|---|---|---|---|---|
| Confidence Level (%) | 88.493 | 91.924 | 94.520 | 96.407 | 98.214 | 99.379 | 99.865 |
Simply paste ledger data from Excel to automate Monetary Unit Sampling (MUS) and Random Sampling. Calculate performance materiality, calculate sample sizes, select items, and evaluate misstatements instantly based on HKICPA Audit Practice Manual (APM) sampling requirements.
NOTE THAT this statistical sampling tool is designed for Variable Sampling (Values) purposes. Users are responsible for ensuring the appropriateness of sampling parameters for their specific audit engagement. All data processing runs exclusively within your local browser environment. We do not collect or store any of your client information.
Best for Directional Testing of Overstatement (Existence/Occurrence). MUS automatically stratifies the population by giving larger dollar items a higher chance of selection. It is highly effective for testing assets and expenses.
Best for Directional Testing of Understatement (Completeness) or when the population has many zero/negative balances. Use this when you need to ensure every physical transaction has an equal chance of selection, regardless of its monetary value (e.g., testing liabilities and revenue).
For TOC, use Attribute Sampling. Sample sizes for TOC are generally fixed based on control frequency (e.g., Daily = 25-40, Monthly = 2-5). If a single deviation is found, the control is usually considered ineffective unless the sample is expanded.
Best for Quantity Count of Physical Inventory. Systematic sampling involves selecting a starting point and then picking every n-th item (e.g., every 10th pallet or every 5th row).
Performance Materiality = Overall Materiality / Inherent Risk Factor
Sample Size = Book Value / Performance Materiality x Sampling Risk Factor
Actual Sample Size = Sample Size + No of Items Above Performance Materiality