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Why is disaggregation important in analytical procedures? What are the limitations of analytical procedures? What is the required analytical review at the final/completion stage? When are analytical procedures more effective than tests of details, and vice versa? How are data analytics changing analytical procedures? How do you use regression or predictive models in substantive analytics? How does the reliability of the data used affect substantive analytical procedures?
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What is the difference between the precision and reliability of an analytical procedure?

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Precision is how closely the expectation predicts the recorded amount—more precise expectations (disaggregated, using strong relationships) detect smaller misstatements. Reliability concerns the trustworthiness of the data used to build the expectation. A procedure is only as effective as both: reliable data and a precise expectation give strong substantive evidence.
Real-world example Monthly, product-level expectations (high precision) from independent data (high reliability) can detect a smaller misstatement than an annual total.

Common follow-ups: How does disaggregation improve precision? | Why does data reliability matter?

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All 18 Analytical Procedures questions