Study Unit 15: questions Flashcards
(44 cards)
When using sampling for substantive tests of details, the auditor is required to do what?
Determine the tolerable misstatement
Project the sample misstatement to the population
Select a representative sample.
What is non sampling risk?
The risk that the auditor reaches an erroneous conclusion for any reason not related to sampling risk.
What is sampling risk?
The risk that the auditor’s conclusion based on a sample may be different from the conclusion if the entire population were subjected to the same audit procedure.
As a result of tests of controls, an auditor underrelies on controls. This incorrect assessment most likely occurred because
Operating effectiveness based on the auditor’s sample is less than the true operating effectiveness of the controls.
In attribute sampling, a 10% change in which factors normally will have the least effect on the size of a statistical sample?
Population size.
A change in the size of the population has a very small effect on the required sample size when the population is large. As the population increases, the sample size also increases but at a decreasing rate.
An advantage of statistical sampling over nonstatistical sampling is that statistical sampling helps an auditor to
Measure the sufficiency of the evidence obtained.
Statistical sampling helps the auditor to design an efficient sample, to measure the sufficiency of the evidence obtained, and to evaluate the sample results. Auditors are required to obtain sufficient appropriate evidence. Sufficiency is the measure of the quantity of evidence. It relates to the design and size of the sample.
An auditor is concerned with two aspects of sampling risk in performing substantive tests of details: the risk of incorrect acceptance and the risk of incorrect rejection. The risk of incorrect acceptance is the risk that:
an auditor erroneously concludes that a material misstatement does not exist when, in fact, it does.
The risk of incorrect rejection is the risk that:
the sample supports the conclusion that a material misstatement does exist when, in fact, it does not.
What is attribute sampling?
refers to an audit sampling application for the purpsoe of estimating the percentage of a population that contains a characteristic (attribute) of interest to the auditor. This involves testing the operating effectiveness of internal control, where, for each transaction included in the sample, the control procedure of interest is either performed approprately or not. For each item in the sample there are only 2 outcomes. (authorized or not, signed or not)
An advantage of statistical over nonstatistical sampling methods in tests of controls is that the statistical methods
Provide an objective basis for quantitatively evaluating sample risks.
In a sampling application, the group of items about which the auditor wants to estimate some characteristic is called the
A.Attribute of interest.
B.Population.
C.Sampling unit.
D.Sample.
Population.
The population is the group of items about which an auditor wishes to draw conclusions. However, the difference between the targeted population (the population about which information is desired) and the sampled population (the population from which the sample is actually drawn) should be understood.
A principal advantage of statistical methods of attribute sampling over nonstatistical methods is that they provide a scientific basis for planning the
Sample size.
Statistical theory permits the auditor to measure sampling risk and to restrict it to an acceptable level. Statistical methods determine the sample size that will accomplish the auditor’s objectives.
Stratifying a population means:
dividing it into subpopulations, thereby permitting application of different sampling techniques to each subpopulation or stratum. Stratifying allows for greater emphasis on larger or more important items.
The use of the ratio estimation sampling technique is most effective when
The calculated audit amounts are approximately proportional to the client’s carrying amounts.
Ratio estimation calculates the population misstatement by multiplying the carrying amount of the population by the ratio of the total audit amount of the sample items to their total carrying amount. The precision is determined by considering the variances of the ratios of carrying amount to audited amount. Thus, the more homogeneous the ratios, the smaller the precision.
In statistical sampling methods used in substantive testing, an auditor most likely would stratify a population into meaningful groups if
The population has highly variable recorded amounts.
The primary objective of stratification is to reduce the effect of high variability by dividing the population into subpopulations. Reducing the effect of the variance within each subpopulation allows the auditor to sample a smaller number of items while holding precision and the confidence level constant
What is unrestricted random sampling?
Unrestricted random sampling means that each item in the population has an equal and nonzero chance of being selected. Sampling with replacement means that an item may be included more than once in the sample. Sampling without replacement removes an item from the population after selection. Thus, sampling without replacement uses information about the population more efficiently. It results in a smaller sample, if other things are held constant, because the sample size formula for sampling with replacement is multiplied by the finite population correction factor (always less than 1.0).
A CPA’s client wishes to determine inventory shrinkage by weighing a sample of inventory items. If a stratified random sample is to be drawn, the strata should be identified in such a way that
Each stratum differs as much as possible with respect to expected shrinkage, but the shrinkages expected for items within each stratum are as close as possible.
When the items in a population are heterogeneous, it may be advantageous to stratify the population into homogeneous subpopulations. Each stratum should differ from the others, but the items within each stratum should be similar.
Stratified mean-per-unit (MPU) sampling is a statistical technique that may be more efficient than unstratified MPU because it usually
Produces an estimate having a desired level of precision with a smaller sample size.
The primary objective of stratification is to reduce the effect of high variability by dividing the population into subpopulations. Reducing the variance within each subpopulation allows the auditor to sample a smaller number of items while holding precision and confidence level constant.
What is the primary objective of monetary-unit sampling (MUS)?
To identify overstatement errors.
MUS gives each monetary unit in the population an equal chance of selection. However, the auditor does not examine an individual monetary unit but uses it to identify an entire transaction or balance to audit (the logical sampling unit). MUS is useful only for tests of overstatements (e.g., of assets) because a systematic selection method is applied (every nth monetary unit is selected). Accordingly, the larger the transaction or balance, the more likely it will be selected. This method is inappropriate for testing a population (e.g., liabilities) when understatement is the primary audit consideration.
To quantify the risk that sample evidence leads to erroneous conclusions about the sampled population,
Each item in the sampled population must have an equal or known probability of being selected.
Probability (random) sampling is used in any sampling plan in which every item in the population has an equal (or known) and nonzero probability of being chosen. A probability sample permits the use of statistical methods based on the laws of probability to quantify an estimate of sampling risk.
The major reason that the difference and ratio estimation methods are expected to produce audit efficiency is that the
Variability of the populations of differences or ratios is less than that of the populations of carrying amounts or audited values.
Difference estimation approximates total misstatement in the population by calculating the mean difference between the audited and carrying amounts in the sample and then multiplying by the number of population items. Ratio estimation approximates the total population misstatement by multiplying the proportion of the sample misstatement times the population carrying amount. The variability in both of these estimates is likely to be smaller than the variability within the population. Because the sample size varies directly with the variability of the population, the use of differences or ratios will usually allow for smaller sample sizes and greater efficiency in sampling.
When assessing the tolerable population deviation rate, the auditor should consider that, although control deviations increase the risks of material misstatement, such deviations do not necessarily result in misstatements. This consideration explains why
A recorded disbursement that does not show evidence of required approval may nevertheless be a transaction that is properly authorized and recorded.
The failure to apply controls does not automatically result in a misstatement of the accounting records. But the deviation does increase the risk of material misstatement.
A test of controls is an application of attribute sampling. The initial size for an attribute sample is based on:
(1) the desired assurance (complement of the risk of overreliance) that the tolerable population deviation rate is not exceeded by the actual rate,
(2) the tolerable population deviation rate,
(3) the expected population deviation rate, and
(4) the population size. However, a change in the size of the population has a very small effect on the required sample size when the population is large. Consequently, population size is often not considered unless it is small.
Does tolerable misstatement relate to test of controls or test of details?
Tests of details.