Chapter 8 [Specialized Audit Tools: Attributes Sampling, Monetary Unit Sampling, and Data-Analytics Tools] Flashcards
(108 cards)
1
Q
A characteristic of the population of interest to the auditor.
A
Attribute
2
Q
A statistical sampling method used to estimate the rate of control procedure failures based on selecting one sample and performing the appropriate audit procedure.
A
Attributes sampling
3
Q
The application of an audit procedure to less than 100% of the items within an account balance or class of transactions for the purpose of evaluating some characteristic of the balance or class.
A
Audit sampling
4
Q
Basic precision
A
The amount of uncertainty associated with testing only a part of the population (sampling risk); calculated as the sampling interval multiplied by a confidence factor.
5
Q
Extremely large and complex data sets that users can analyze to reveal patterns and associations; often so large that users cannot efficiently analyze it using tools such as Excel because the data overloads the system.
A
Big data
6
Q
A sampling technique that involves selecting a sample that consists of contiguous population items, such as selecting transactions by day or week.
A
Block sampling
7
Q
A digital accounting ledger of transactions that can be programmed to record financial transactions among multiple parties. ____________ enables smart contracts that include coded instructions for the blockchain ledger about when a contract will occur, the parties involved in the contract, and the payment terms.
A
Blockchain
8
Q
Electronic computer programs software companies are developing and marketing that enable organizations to use data analytics and big data by providing online analytical processing, information transformation (e.g., dashboards that display key performance indicators), and data management and security.
A
Business intelligence (BI) platforms
9
Q
A process that includes investigating new patterns in data that might change the way that the organization organizes and uses its data.
A
Classification analyses
10
Q
A broad construct referring to both qualitative and quantitative analysis tools that enable a decision maker to extract data, categorize it, identify patterns within it, and use it to enhance efficiency and effectiveness in decision making.
A
Data analytics
11
Q
Qualitative and quantitative techniques and processes that auditors use to enhance their productivity and effectiveness; auditors extract, categorize, identify, and analyze patterns or trends in the data. They vary according to organizational requirements.
A
Data-analytics tools
12
Q
Information that companies use to generate revenue; can include, for example, output files from customers’ use of an app, information from systems in which customers interact with the company’s website, and databases that the company uses to store information about its business.
A
Data assets
13
Q
Activities that users complete to retrieve data (e.g., bar coding).
A
Data capture
14
Q
An inventory of data available to an organization that may include data on suppliers, employees, production, sales, and fixed assets, among others; assists data stewards in managing their respective data assets.
A
Data catalog
15
Q
An organization that manages hardware, software, air conditioning, backup systems, and communication and security equipment for multiple organizations; allow organizations to store data “off-site” to prevent misuse, manipulation, or destruction.
A
Data center
16
Q
Activities that users complete to correct or remove erroneous data (e.g., contradictory data, input keying mistakes, duplicate data, missing information, and inappropriate changes to the data).
A
Data cleaning
17
Q
Activities that involve creating, organizing, and maintaining data sets so that the appropriate users are aware of the data and can access them.
A
Data curation
18
Q
Helps users understand the structure and content of a database, including the name of the data, its description, relationships among various related data, and access rights.
A
Data dictionary
19
Q
An electronic exploitation that involves the perpetrator embedding seemingly valid data that enables malicious computer codes to exploit weaknesses in the computer system.
A
Data-driven attack
20
Q
Gaining an understanding of data by using techniques such as path analysis, classification, and visualization.
A
Data exploration
21
Q
The exercise of authority and control (e.g., planning and monitoring) over the manner in which an organization manages its data assets.
A
Data governance
22
Q
A conceptual modeling that outlines an organization’s decisions about data that it will collect and control and metrics around data accuracy, quality, timeliness, and usage.
A
Data governance framework
23
Q
The process of sorting through large data sets to identify patterns, measure and predict trends, and establish relationships to solve problems through data analytics. When conducting data mining, users create and analyze data.
A
Data mining
24
Q
A process by which data scientists define and analyze data requirements that they need to support the business processes through data-producing information systems within organizations.
A
Data modeling
25
An interdisciplinary field about scientific methods, processes, and information systems that aims to help users gain insights from complex and often unstructured data.
Data science
26
An individual who oversees data usage and security policies and acts as a liaison between the IT department and the remainder of the organization; curate data assets.
Data steward
27
Integrating data and models to solve problems or make decisions in an organization.
Deploying models
28
An anticipation of the deviation rate in the entire population. Also referred to as the expected failure rate.
Expected failure rate
29
The level of misstatement that the auditor expects to detect, and it is based on projected misstatements in prior-year audits, results of other substantive tests, professional judgment, and knowledge of changes in personnel and the accounting system.
Expected misstatement
30
An anticipation of the deviation rate in the entire population. Also referred to as the expected failure rate.
Expected population deviation rate
31
(also referred to as known misstatements ) Misstatements that have been specifically identified and about which there is no doubt.
Factual misstatements
32
A nonstatistical sample selection method that attempts to approximate a random selection by selecting sampling units without any conscious bias, or special reason for including or omitting certain items from the sample.
Haphazard sampling
33
An increase in the total estimated misstatement caused by the statistical properties of misstatements detected in the lower stratum.
Incremental allowance for sampling risk
34
An individual unit in an overall performance measurement system; they differ based on the area in the organization that deploys them.
Key performance indicator (KPI)
35
(also referred to as factual misstatements ) Misstatements that have been specifically identified and about which there is no doubt.
Known misstatements
36
See Projected misstatement.
Likely misstatement
37
The balance or transaction that includes the selected dollar in a monetary unit sample.
Logical unit
38
Items that are not in the top stratum.
Lower stratum
39
An error, either intentional or unintentional, that exists in a transaction or financial statement account balance. For substantive sampling purposes, a misstatement involves differences between recorded values and audited values.
Misstatement
40
(also referred to as probability proportional to size sampling ) A sampling method based on attributes estimation sampling but involving dollar misstatements rather than failure rates.
Monetary unit sampling (MUS)
41
The best estimate of the actual amount of dollar misstatements in the population based on projecting the sample results to the population. The projected misstatement is calculated as the sampling interval multiplied by the tainting percentage.
Most likely misstatement
42
The risk that the auditor reaches an erroneous conclusion for any reason not related to sampling risk.
Nonsampling risk
43
The application of auditor judgment and experience in a sample application to assist the auditor in determining an appropriate sample size and in evaluating the sample results.
Nonstatistical sampling
44
A process that involves looking for instances in which one construct or measure predicts one that follows another.
Path analysis
45
A group of transactions or the items that make up an account balance for which the auditor wants to estimate some characteristic, such as the effectiveness of a control procedure or estimating the extent of misstatement in an account.
Population
46
A sampling selection method in which each item in the population has a probability of being included in the sample proportionate to the dollar value of the item. Monetary unit sampling uses this method to select a sample and is considered a subset of PPS sampling.
Probability proportional to size (PPS) sampling
47
The best estimate of the actual amount of dollar misstatements in the population based on projecting the sample results to the population. The projected misstatement is calculated as the sampling interval multiplied by the tainting percentage.
Projected misstatement
48
(also referred to as the risk of assessing control risk too high ) The risk that the auditor will conclude that the state of internal controls is not effective when internal controls are actually effective.
Risk of assessing control risk too high
49
(also referred to as the risk of assessing control risk too low ) The risk that the auditor will conclude that the state of internal controls is effective when internal controls are actually not effective.
Risk of assessing control risk too low
50
(also referred to as the risk of assessing control risk too low ) The risk that the auditor will conclude that the state of internal controls is effective when internal controls are actually not effective.
Risk of incorrect acceptance of internal control reliability
51
The risk that the auditor will conclude that the account balance does not contain a material misstatement when the account balance actually does contain a material misstatement.
Risk of incorrect acceptance of book value
52
The risk that the auditor will conclude that the account balance contains a material misstatement when the account balance actually does not contain a material misstatement.
Risk of incorrect rejection of book value
53
(also referred to as the risk of assessing control risk too high ) The risk that the auditor will conclude that the state of internal controls is not effective when internal controls are actually effective.
Risk of incorrect rejection of internal control reliability
54
Calculated by dividing the population size by the desired sample size.
Sampling interval
55
The risk that the auditor’s conclusion based on a sample might be different from the conclusion the auditor would reach if the test were applied in the same way to the entire population.
Sampling risk
56
The individual items to be tested.
Sampling units
57
Results in knowingly or unknowingly creating unrepresentative samples.
Selection bias
58
Selecting a random sample by matching random numbers generated by a computer or selected from a random-number table with, for example, document numbers such as an invoice or a purchase order.
Simple random sampling
59
The application of probability theory and statistical inference, along with auditor judgment and experience, in a sample application to assist the auditor in determining an appropriate sample size and in evaluating the sample results.
Statistical sampling
60
Dividing the population into two or more subgroups.
Stratification
61
This sampling technique involves systematic sampling in which the first item is selected randomly from the interval.
Systematic random sampling
62
This sampling technique involves dividing the number of physical units in the population by the sample size to determine a uniform interval; a random starting point is selected in the first interval and one item is selected throughout the population at each of the uniform intervals after the starting point.
Systematic sampling
63
The percentage of misstatement present in a logical unit, such as the sample item’s book value. The tainting percentage equals the amount of misstatement in the item divided by the item’s recorded amount.
Tainting percentage
64
A rate of deviation set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the rate of deviation set by the auditor is not exceeded by the actual rate of deviation in the population. Also referred to as the tolerable failure rate.
Tolerable failure rate
65
A monetary amount set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the monetary amount set by the auditor is not exceeded by the actual misstatement in the population. In practical terms, a tolerable misstatement is the maximum amount of misstatement the auditor can accept in the population without requiring an audit adjustment or a qualified audit opinion.
Tolerable misstatement
66
A rate of deviation set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the rate of deviation set by the auditor is not exceeded by the actual rate of deviation in the population. Also referred to as the tolerable failure rate.
Tolerable rate of deviation
67
Population items whose book values exceed the sampling interval and are therefore all included in the sample. The top stratum consists of all account balances exceeding a specific dollar amount.
Top stratum
68
A process that includes the process of understanding the significance of and patterns in data by placing it in a visual context.
Visualization
69
Sampling can be used for both tests of control and substantive tests of account balances and assertions
| T or F?
TRUE
70
Auditors can use sampling for testing either the effectiveness of controls (attributes sampling) or direct tests of account balances and assertions (monetary unit sampling)
| T or F?
TRUE
71
For which of the following auditing procedures would sampling be most appropriate?
a. Examining documents
b. Inquiring of management
c. Observing controls being completed
d. Conducting analytical procedures
a
72
Which of the following activities would be most likely accomplished using sampling?
a. Sorting a file to identify the largest items
b. Scanning for unusual transactions
c. Selecting items and tracking them back to source documents
d. Footing the file
c
73
Sampling risk is the risk that the auditor's conclusion based on a sample might be different from the conclusion that would be reached if the audit procedure was applied in the same way to the entire population.
| T or F?
TRUE
74
The risk of incorrect acceptance of internal control reliability is a risk that the auditor will conclude that an internal control is not effective when the internal control is effective
| T or F?
FALSE
75
Which of the following questions would an auditor ask when sampling to perform tests of control?
a. Which population and sampling unit should be tested, and what characteristics should be examined?
b. How many items should be selected for audit testing?
c. Which items should be included in the sample?
d. What inferences can be made about the overall population from the sample?
e. All of the above
e
76
Refer to Exhibit 8.2 and determine which of the following terms match this definition:
*The risk that the auditor will conclude that internal controls are effective when internal controls are actually not effective.*
a. The risk of incorrect acceptance of internal control reliability
b. The risk of incorrect acceptance of book value
c. The risk of incorrect rejection of internal control reliability
d. The risk of incorrect rejection of book value
e. None of the above
a
77
A benefit of nonstatistical sampling as compared to statistical sampling is that the sample size can be significantly smaller, thereby making the audit more efficient
| T or F?
FALSE
78
A benefit of statistical sampling as compared to nonstatistical sampling is that less auditor judgement is required because the auditor can leverage the power of probability theory
| T or F?
FALSE
79
Refer to Exhibit 8.4 and determine which of the following statements is true.
a. In nonstatistical sampling, sample size is determined by auditor judgment
b. In statistical sampling, the sample must be randomly selected to give each unit in the population an equal chance to be included in the sample
c. In nonstatistical sampling, evaluation is based on auditor judgment and projections are based on sample results
d. All of the above are true
e
80
Which of the following statements is false?
a. When properly used, either nonstatistical or statistical sampling can be effective in providing sufficient appropriate audit evidence
b. Statistical sampling allows the auditor to measure the risk of making an incorrect inference about the population from which the sample is taken, whereas nonstatistical sampling does not allow for such measurement
c. Nonstatistical sampling may help avoid second guessing by regulators or jurors should those parties question the quality of sampling with audit judgment
d. Combining statistical sampling with audit judgment generally produces a higher quality audit conclusion than using audit judgment alone
e. All of the above are false
c
81
Attributes sampling is a statistical sampling method used to estimate the rate of control procedure failures based on selecting a sample and performing the appropriate audit procedure
| T or F?
TRUE
82
In attributes sampling, the attribute of interest is an individual dollar amount in the population
| T or F?
FALSE
83
Use Exhibit 8.5 to determine which of the following statements is false
a. As tolerable deviation rate rises, the sample size decreases
b. As the expected deviation rate rises, the sample size decreases
c. If the auditor accepts a 5% risk of overreliance, a 7% tolerable deviation rate, and expects a deviation rate of 2.5%, the sample size will equal 109
d. If the auditor accepts a 10% risk of overreliance, a 7% tolerable deviation rate, and expects a deviation rate of 2.5%, the sample size will be a number less than 109
e. All of the above are false
b
84
In attributes sampling, which of the following will not affect the sample size?
a. The risk of incorrect rejection of book value.
b. Sampling risk.
c. The tolerable rate of deviation.
d. The expected population deviation rate.
a
85
Block sampling involves selecting a sample that consists of contiguous population items, such as selecting transactions by day or week.
| T or F?
TRUE
86
Haphazard sampling is a statistical sample selection method that attempts to approximate a random selection by selecting sampling units without any conscious bias, or special reason for including or omitting certain items from
the sample.
| T or F?
FALSE
87
Refer to Exhibit 8.6. Assume a 5% risk of overreliance, a tolerable deviation rate of 8%, a sample size of 100, and that the number of deviations is five. What is the upper limit of the possible deviation rate, and what does it mean?
a. 10.3%. The auditor is 95% confident that the real error rate in the population is no greater than 10.3%.
b. 10.3%. The auditor is 95% confident that the real error rate in the population is no greater than 5%.
c. 5%. The auditor is 92% confident that the real error rate in the population is no greater than 10.3%.
d. 5%. The auditor is 92% confident that the real error rate in the population is no greater than 5%.
a
88
Consider the case whereby the risk of overreliance is 5%, the sample size is 20, and the auditor detects no deviations in the operation of the control. What can the auditor conclude?
a. This is good news; no deviations were found, so we conclude that the control is working effectively.
b. The upper limit of deviations is 14%, so we conclude that the control is not working effectively.
c. If we doubled the sample size, the upper limit of deviations would decrease by about half.
d. One of the above a-c.
e. Two of the above a-c.
e
89
When the auditor detects control deviations, it is best to evaluate them quantitatively rather than qualitatively.
| T or F?
FALSE
90
When using nonstatistical sampling, the auditor cannot quantitatively assess the risk of making an incorrect inference based on the sample results.
| T or F?
TRUE
91
Which of the following relationships is inaccurate?
a. High tolerable deviation rate=smaller sample; Low tolerable deviation rate=larger sample
b. Low expected population deviation rate=small sample; High expected population deviation rate=larger sample
c. Low sampling risk=small sample; High sampling risk=larger sample
d. Population size has little effect on sample size
c
92
The auditor should not pursue which of the following options when a control is ineffective?
a. Identify a compensating control.
b. Take a larger sample.
c. Assess control risk as lower than originally planned and change the audit approach accordingly.
d. Analyze the nature of the control deviations and identify implications.
c
93
Top-stratum items are population items whose book values exceed the sampling interval and are therefore excluded from the sample
| T or F?
FALSE
94
The division of a population into two or more subgroups is referred to as stratification.
TRUE
95
Which of the following definitions is true?
a. Factual misstatement—A misstatement that has been specifically identified and about which there is no doubt.
b. Projected misstatement—The auditor’s best estimate of the misstatement in a given population based on projecting the sample results to the population.
c. Tolerable misstatement—A monetary amount set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the monetary amount set by the auditor is not exceeded by the actual misstatement in the population.
d. Expected misstatement—The level of misstatement that the auditor expects to detect.
e. All of the above are true.
e
96
Which of the following statements is false?
a. Top-stratum items are population items whose book values exceed the sampling interval and are therefore all included in the sample.
b. Because the auditor knows the amount of errors in the top stratum (all items were evaluated), no estimate of errors is required for the top stratum.
c. Stratification of the population into several subpopulations generally reduces audit efficiency.
d. Sampling evaluation reflects the sum of top-stratum misstatements and the projected misstatement derived from lower-stratum items.
e. None of the above are false.
c
97
One strength of MUS is that it automatically selects a sample in proportion to an item’s dollar amount, thus providing automatic stratification of the sample.
| T or F?
TRUE
98
The population for MUS is defined as the number of dollars in the population being tested. Each dollar in the population has an equal chance of being chosen, but each dollar chosen is associated with a tangible item such as a customer’s balance or an inventory item, so
items with more dollars have a greater likelihood of being selected.
| T or F?
TRUE
99
Refer to Exhibit 8.7. Assume that the risk of incorrect acceptance is 10%, tolerable misstatement is 5% of population dollars, and expected misstatement is 30% of tolerable misstatement (in other words, 1.5% of the
population dollars). What is the minimum sample size that the auditor should use?
a. 28
b. 87
c. 120
d. 162
b
100
Which of the following represents the calculation of the sampling interval?
a. Tolerable error / Risk of incorrect acceptance.
b. Sample size / Population size.
c. Tolerable error * Risk of incorrect acceptance.
d. Population size / Sample size.
d
101
The projected misstatement for items in the upper stratum is calculated as the sampling interval multiplied by the tainting percentage.
| T or F?
FALSE
102
Projected errors for items in the top stratum equal basic precision multiplied by a confidence factor.
| T or F?
FALSE
103
Which of the following statements is false with respect to basic precision?
a. Basic precision represents the increase in the total estimated misstatement caused by the statistical properties of misstatements detected in the lower stratum.
b. Basic precision is the amount of uncertainty associated with testing only a part of the population (sampling risk).
c. Basic precision is the amount of error you are confident of not exceeding if no errors are detected in the sample.
d. Basic precision is calculated as the sampling interval multiplied by a confidence factor.
a
104
In a MUS sample, the total estimated misstatement calculation includes which of the following amounts?
a. The factual misstatement in the top-stratum.
b. Basic precision.
c. The projected misstatement in the lower stratum.
d. An incremental allowance for sampling risk in the lower stratum.
e. All of the above.
e
105
Benford’s Law helps predict frequency patterns of deviations of controls.
| T or F?
FALSE
106
Data analytics is a broad construct referring to both qualitative and quantitative analysis tools that enable a decision maker to extract data, categorize it, identify patterns within it, and use it to enhance efficiency and effectiveness in decision making.
| T or F?
TRUE
107
The acronym KPI relates to which of the following phrases?
a. Key Profitability Indicator
b. Key Performance Indicator
c. Known Performance Increment
d. Known Profitability Increment
b
108
To test the existence assertion for sales, which of the following data analytics tools might you use?
a. Compare sales invoices with shipping documents.
b. Compare sales invoices with sales contracts.
c. Analyze data around year-end to ensure that sales are recorded in the correct period.
d. Two of the above (a-c).
e. All of the above (a-c).
b
