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In evaluating the results of an attribute sample, the auditor can conclude that there are no material weaknesses in internal controls only when?

1) The expected error is equal to or less than the tolerable error.
2) No internal control deviations were found in the sample.
3) The confidence level is greater than or equal to 90.
4) The tolerable error is equal to or greater than the computed upper deviation rate.

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Final answer:

An auditor can conclude no material weaknesses in internal controls when the computed upper deviation rate is less than or equal to the tolerable error, implying the internal control deviations are within acceptable limits. Confidence levels and sample sizes are crucial in determining the precision and reliability of these conclusions.

Step-by-step explanation:

In evaluating the results of an attribute sample, the auditor can conclude that there are no material weaknesses in internal controls only when the tolerable error is equal to or greater than the computed upper deviation rate. Tolerable error is the maximum error in the population that the auditor is willing to accept, and the upper deviation rate is the highest estimated rate of deviation from a prescribed internal control procedure. When the computed upper deviation rate is less than or equal to the tolerable error, the auditor may conclude that the controls are effective or that any deviations are not material.

Confidence level is also an integral part of concluding on internal controls. The higher the confidence level, the more assurance an auditor has in the sampling results. For instance, a 90% confidence level means that we would expect 90% of the confidence intervals created from such samples to capture the true population parameter being estimated.

If an auditor wanted to ensure a lower error bound while maintaining the same level of confidence, they would need to either increase the sample size or choose a more precise sampling method. Various factors that could affect the outcome of a survey or an audit include the inherent variability of the sample due to the underlying distribution, and other non-sampling errors which may not be covered by the margin of error.

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