Statistical Sampling and Hypothesis Testing Flashcards
6 cards from real ADA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Statistical Sampling and Hypothesis Testing flashcards as text
Which sampling method ensures every item in the population has an equal chance of being selected for audit testing?
Answer: Simple random sampling
Simple random sampling gives every population item an equal probability of selection, eliminating selection bias.
In hypothesis testing for audit analytics, what does a p-value of 0.03 indicate when the significance level is 0.05?
Answer: Reject the null hypothesis
Since 0.03 < 0.05, the result is statistically significant and the auditor rejects the null hypothesis.
Which type of sampling divides a population into subgroups and samples from each subgroup proportionally?
Answer: Stratified random sampling
Stratified random sampling segments the population into homogeneous strata and draws samples from each, improving precision.
A Type I error in audit hypothesis testing occurs when the auditor:
Answer: Concludes a misstatement exists when it does not
A Type I error (false positive) means rejecting a true null hypothesis — concluding a problem exists when the population is actually clean.
Monetary Unit Sampling (MUS) is best suited for audit populations where:
Answer: Higher-value items should have a greater chance of selection
MUS weights selection probability by dollar amount, automatically giving larger balances a higher chance of being tested.
When determining sample size for statistical sampling in an audit, increasing the desired confidence level will:
Answer: Increase the required sample size
Higher confidence requires more evidence, so the required sample size increases to achieve that level of assurance.