ADA Statistical Sampling and Hypothesis Testing

Question 1

Which sampling method ensures every item in the population has an equal chance of being selected for audit testing?

Accepted Answer

Simple random sampling

Answer

Simple random sampling gives every population item an equal probability of selection, eliminating selection bias.

Question 2

In hypothesis testing for audit analytics, what does a p-value of 0.03 indicate when the significance level is 0.05?

Accepted Answer

Reject the null hypothesis

Answer

Since 0.03 < 0.05, the result is statistically significant and the auditor rejects the null hypothesis.

Question 3

Which type of sampling divides a population into subgroups and samples from each subgroup proportionally?

Accepted Answer

Stratified random sampling

Answer

Stratified random sampling segments the population into homogeneous strata and draws samples from each, improving precision.

Question 4

A Type I error in audit hypothesis testing occurs when the auditor:

Accepted Answer

Concludes a misstatement exists when it does not

Answer

A Type I error (false positive) means rejecting a true null hypothesis — concluding a problem exists when the population is actually clean.

Question 5

Monetary Unit Sampling (MUS) is best suited for audit populations where:

Accepted Answer

Higher-value items should have a greater chance of selection

Answer

MUS weights selection probability by dollar amount, automatically giving larger balances a higher chance of being tested.

ADA - Audit Data Analytics Certification Practice Test