Data Analytics for Accounting Vernon Richardson 1st Edition- Test Bank
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Sample Test
Data Analytics for Accounting, 1e (Richardson)
Chapter 3 Modeling and Evaluation: Going from
Defining Business Problems and Data Understanding to Analyzing Data and Answering
Questions
1) Benford’s Law is an absolute and all data must conform.
Answer: FALSE
Difficulty: 1 Easy
Topic: Example of Profiling in Auditing and Continuous
Auditing
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
2) A decision tree can be used to divide data into smaller
groups.
Answer: TRUE
Difficulty: 1 Easy
Topic: Classification Terminology
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
3) Data reduction is a data approach used to reduce the amount
of information that needs to be considered to focus on the most critical items.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
4) Regression is a data approach used to estimate or predict,
for each unit, the numerical value of some variable using some type of statistical
model.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
5) Link prediction is a data approach used to estimate or
predict, for each unit, the numerical value of some variable using some type of
statistical model.
Answer: FALSE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
6) Existing data that has been manually evaluated and assigned a
class is often referred to as test data.
Answer: FALSE
Difficulty: 2 Medium
Topic: Classification Terminology
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
7) Co-occurrence grouping could be used to match vendors by
geographic region.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
8) Fuzzy matching is a data approach used to identify similar
individuals based on data known about them.
Answer: FALSE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
9) Alibaba and its attempt to identify seller and customer fraud
based on various characteristics known about them is an example of similarity
matching.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
10) Fuzzy matching is a computer-assisted technique of finding
matches that are less than 100 percent perfect by finding correspondences
between portions of the text of each potential match.
Answer: TRUE
Difficulty: 1 Easy
Topic: Example of Data Reduction in Internal and External
Auditing
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
11) The P in IMPACT Cycle represents performing test plan.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
12) Clustering is a data approach used to divide individuals
into groups in a useful or meaningful way.
Answer: TRUE
Difficulty: 1 Easy
Topic: Clustering Data Approach
Learning Objective: 03-05 Understand the clustering
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
13) An example of classification would be a credit card company
flagging a transaction as being approved or potentially being fraudulent and
denying payment.
Answer: TRUE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
14) The data approach used to characterize the typical behavior
of an individual, group or population by generating summary statistics about
the data is referred to as classification.
Answer: TRUE
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
15) XBRL is a global standard for exchanging financial reporting
information that uses XML.
Answer: TRUE
Difficulty: 1 Easy
Topic: Examples of Data Reduction in Other Accounting
Areas
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
16) XBRL is used to facilitate the exchange of financial
reporting information between the company and the Securities and Exchange
Commission.
Answer: TRUE
Difficulty: 1 Easy
Topic: Examples of Data Reduction in Other Accounting
Areas
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
17) Data profiling typically involves unstructured data.
Answer: FALSE
Difficulty: 1 Easy
Topic: Profiling Data Approach
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
18) A target is a manually assigned category applied to a record
based on an event.
Answer: FALSE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
19) When considering a question such as “Do our customers form
natural groups based on similar attributes?” you would use an unsupervised
approach.
Answer: TRUE
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
20) Co-occurrence grouping is an example of a supervised
approach.
Answer: FALSE
Difficulty: 1 Easy
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
BB Industry
21) All of the following are examples of a supervised approach
to evaluation data except:
1. A)
Causal modeling
2. B)
Data reduction
3. C)
Link prediction
4. D)
Regression
Answer: B
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
22) All of the following are examples of an unsupervised
approach to evaluation data except:
1. A)
Similarity matching
2. B)
Clustering
3. C)
Profiling
4. D)
Co-occurrence grouping
Answer: A
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
23) Which of the following best describes an unsupervised
approach to the evaluation of data?
1. A)
Data exploration that is free from oversight by a superior
2. B)
Data exploration that examines the relationships between variables that are
hypothesized to exist
3. C)
Data exploration that looks for potential patterns of interest
4. D)
Data exploration that is conducted with direct oversight by a superior
Answer: C
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
24) Which of the following best describes a supervised approach
to the evaluation of data?
1. A)
Data exploration that is free from oversight by a superior
2. B)
Data exploration that is conducted with direct oversight by a superior
3. C)
Data exploration that examines the relationships between variables that are
hypothesized to exist
4. D)
Data exploration that looks for potential patterns of interest
Answer: C
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
25) Which approach to data analytics attempts to assign each
unit in a population into a small set of categories?
1. A)
Classification
2. B)
Regression
3. C)
Similarity matching
4. D) Co-occurrence
grouping
Answer: A
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
26) Which approach to data analytics attempts to divide
individuals into groups in a useful or meaningful way?
1. A)
Clustering
2. B)
Data reduction
3. C)
Similarity matching
4. D)
Co-occurrence grouping
Answer: A
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
27) Which approach to data analytics attempts to identify
similar individuals based on data known about them?
1. A)
Classification
2. B)
Clustering
3. C)
Similarity matching
4. D)
Co-occurrence grouping
Answer: C
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
28) Which approach to data analytics attempts to discover
associations between individuals based on transactions involving them?
1. A)
Classification
2. B)
Regression
3. C)
Similarity matching
4. D)
Co-occurrence grouping
Answer: D
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
29) Which approach to data analytics attempts to forecast a
relationship between two data items?
1. A)
Link prediction
2. B)
Regression
3. C)
Similarity matching
4. D)
Co-occurrence grouping
Answer: A
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
30) Which approach to data analytics attempts to predict, for
each unit, the numerical value of some variable?
1. A)
Classification
2. B)
Regression
3. C)
Similarity matching
4. D)
Link prediction
Answer: B
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
31) Which approach to data analytics attempts to characterize
the typical behavior of an individual, group or population by generating
summary statistics about the data?
1. A)
Classification
2. B)
Regression
3. C)
Profiling
4. D)
Link prediction
Answer: C
Difficulty: 2 Medium
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
32) ________ refers to data that is stored in a database or
spreadsheet that is readily searchable.
1. A)
Training data
2. B)
Unstructured data
3. C)
Structured data
4. D)
Test data
Answer: C
Difficulty: 2 Medium
Topic: Profiling Data Approach
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
33) Using social media to look for relationships between related
parties that are not otherwise disclosed to identify related party transactions
is an example of ________.
1. A)
Classification
2. B)
Regression
3. C)
Profiling
4. D)
Link prediction
Answer: D
Difficulty: 3 Hard
Topic: Performing the Test Plan: Defining Data Analytics
Approaches
Learning Objective: 03-01 Define Data Analytics
Approaches.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
34) Data profiling is used to assess data quality and internal
controls. It typically involves the following steps except:
1. A)
Filter the results.
2. B)
Identify the objects or activity you want to profile.
3. C)
Determine the types of profiling you want to perform.
4. D)
Set boundaries or thresholds for the activity.
Answer: A
Difficulty: 2 Medium
Topic: Profiling Data Approach
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
35) Regression analysis typically involves the following
steps except:
1. A)
Identify the variables that might predict an outcome.
2. B)
Identify the parameters of the model.
3. C)
Set boundaries or thresholds.
4. D)
Determine the functional form of the relationship.
Answer: C
Difficulty: 2 Medium
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
36) Data reduction typically involves the following steps except:
1. A)
Identify the attribute you would like to reduce or focus on.
2. B)
Identify the parameters of the model.
3. C)
Filter the results.
4. D)
Interpret the results.
Answer: B
Difficulty: 2 Medium
Topic: Data Reduction Data Approach
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
37) When working with a predictive model, underfitting the data
is most likely caused by ________.
1. A) an
overly complex model
2. B) an
overly simple model
3. C)
over pruning the data
4. D) a
lack of data reduction
Answer: B
Difficulty: 2 Medium
Topic: Evaluating Classifiers
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
38) In general, the more complex the model, the greater the
chance of ________.
1. A)
Overfitting the data
2. B)
Underfitting the data
3. C)
Pruning the data
4. D)
The need to reduce the amount of data considered
Answer: A
Difficulty: 2 Medium
Topic: Evaluating Classifiers
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
39) While overfitting data could lead to an error rate of 0
(zero), it is unlikely that you would be able to ________ your results.
1. A)
define
2. B)
specify
3. C)
articulate
4. D)
generalize
Answer: D
Difficulty: 3 Hard
Topic: Evaluating Classifiers
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
40) Which of the following best describes an independent
variable?
1. A)
Output
2. B)
Input
3. C)
Application
4. D)
Operation
Answer: B
Difficulty: 1 Easy
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
41) Which of the following best describes a dependent variable?
1. A)
Output
2. B)
Input
3. C)
Application
4. D)
Operation
Answer: A
Difficulty: 1 Easy
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
42) Understanding and predicting inventory obsolescence is an
important determination for retail companies. When using competitor selling
prices to estimate the inventory obsolescence reserve, the inventory obsolescence
reserve represents which of the following?
1. A)
Independent variable
2. B)
Dependent variable
3. C)
Function
4. D)
Statistical Model
Answer: B
Difficulty: 3 Hard
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and classification
approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
43) Understanding and predicting warranty expense is an
important determination for manufacturing firms. When using historical claims
data to estimate the current period’s warranty expense, the historical claims
data represents which of the following?
1. A)
Independent variable
2. B)
Dependent variable
3. C)
Function
4. D)
Statistical Model
Answer: A
Difficulty: 3 Hard
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
44) One of the key tasks of bank auditors is to consider the
amount of the loan loss reserve. When developing a model to estimate the
current year’s loan loss reserve amount, which of the following would be least
likely to be included as an independent variable?
1. A)
Original loan approval amount
2. B)
Customer loan history
3. C)
Current aged loans
4. D)
Collections success
Answer: A
Difficulty: 3 Hard
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
45) The short surveys regarding dining preferences requested at
the bottom of the restaurant bill are an example of which data approach?
1. A)
Clustering
2. B)
Regression
3. C)
Similarity matching
4. D)
Link prediction
Answer: A
Difficulty: 2 Medium
Topic: Clustering Data Approach
Learning Objective: 03-05 Understand the clustering approach
to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
46) Retail stores often request customers’ zip codes at the end
of a sales transaction. This is an example of which data approach?
1. A)
Clustering
2. B)
Regression
3. C)
Similarity matching
4. D)
Classification
Answer: A
Difficulty: 2 Medium
Topic: Clustering Data Approach
Learning Objective: 03-05 Understand the clustering
approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
47) ________ is existing data that has been manually
evaluated and assigned a class and ________ is existing data used to
evaluate the model.
1. A)
Test data; Training data
2. B)
Training data; Test data
3. C)
Structured data; Unstructured data
4. D)
Unstructured data; Structured data
Answer: B
Difficulty: 1 Easy
Topic: Classification Terminology
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
48) ________ mark the split between one class and another.
1. A)
Decision trees
2. B)
Identifying questions
3. C)
Decision boundaries
4. D)
Linear classifiers
Answer: C
Difficulty: 1 Easy
Topic: Classification Terminology
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
49) ________ states that in many naturally occurring collections
of numbers, the leading significant digit is likely to be small.
1. A)
Leading digits hypothesis
2. B)
Moore’s law
3. C)
Benford’s law
4. D)
Classification
Answer: C
Difficulty: 2 Medium
Topic: Example of Profiling in Auditing and Continuous
Auditing
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
50) Unaware of data analysis tools available to the internal
auditors, a store employee frequently processes cash returns without a receipt
for $99, which is just below the amount requiring manager approval of $100. An
analysis using which of the following would likely (and quickly) identify the
employee’s fraudulent behavior?
1. A)
Leading digits hypothesis
2. B)
Moore’s law
3. C)
Benford’s law
4. D)
Clustering
Answer: C
Difficulty: 3 Hard
Topic: Example of Profiling in Auditing and Continuous
Auditing
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
51) What is the difference between structured data and
unstructured data? Provide an example of each.
Answer: Answers may vary slightly!
- Structured
data are data that are organized and reside in a fixed field with a record
or a file. Examples include: Relational database, spreadsheet, or other
formats that are readily searchable by search algorithms.
- Unstructured
data are data that either does not have a pre-defined data model or is not
organized in a pre-defined manner. Examples include: Photographs,
Instagram, Twitter, or satellite Images.
Difficulty: 2 Medium
Topic: Profiling Data Approach; Data Reduction Data
Approach
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics; 03-03 Describe the data reduction approach to Data Analytics
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
BB Industry
52) Decision trees are used to divide data into smaller groups
by splitting the data at each branch into two or more groups. However, this
method could lead to unintended consequences if the decision tree is not
pruned. Describe the pruning process, when it can occur and the benefits of
using it.
Answer: Answers will vary but should include some of these
items.
- Pruning
removes branches from a decision tree to avoid overfitting the model.
o Prepruning occurs during the model
generation. The model stops creating new branches when the information
usefulness of an additional branch is low.
o Postpruning evaluates the complete model
and discards branches after the fact.
Difficulty: 3 Hard
Topic: Classification Terminology
Learning Objective: 03-03 Describe the data reduction
approach to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking; Knowledge Application
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
53) Chapter 3 discussed 5 (five) data analytics approaches or
techniques are most common to address our accounting questions. List and define
3 of the 5 data analytics approaches. Next, describe how each of the 3 data
analytics approaches you list could be used by credit card companies to
identify fraudulent credit card activity.
Answer:
- Classification: A data
approach used to assign each unit in a population into a few categories
potentially to help with predictions.
o Credit card companies establish models to
predict fraud and decide whether to accept or reject a proposed credit card
transaction. A potential model may be the following:
§
Transaction approval =f(location
of current transaction, location of last transaction, amount of current
transaction, prior history of travel of credit card holder, etc.)
- Clustering: data
approach used to divide individuals (like customers) into groups (or
clusters) in a useful or meaningful way.
o Heat map could be used to determine if
purchases are outside of the person’s “home” region
- Data
reduction: A
data approach used to reduce the amount of information that needs to be
considered to focus on the most critical items (i.e., highest cost,
highest risk, largest impact, etc.).
o Looking at the only transactions over a
certain dollar threshold
- Profiling: A data
approach used to characterize the “typical” behavior of an individual,
group or population by generating summary statistics about the data
(including mean, standard deviations, etc.).
o Looking to characteristics such as the
amounts, totals, and types of expenditures to identify potential anomalies. For
example, depending on the individual’s spending history, a $1,000 purchase at
Spools and Bolts (a quilting shop) might not be an anomaly.
- Regression: A data
approach used to estimate or predict, for each unit, the numerical value
of some variable using some type of statistical model.
o Credit card companies establish models to
predict fraud and decide whether to accept or reject a proposed credit card
transaction. A potential model may be the following:
§
Transaction approval =f(location
of current transaction, location of last transaction, amount of current
transaction, prior history of travel of credit card holder, etc.)
Difficulty: 3 Hard
Topic: Profiling Data Approach; Data Reduction Data
Approach; Regression Data Approach; Clustering Data Approach
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics; 03-03 Describe the data reduction approach to Data
Analytics; 03-04 Understand the regression and classification approach to Data
Analytics; 03-05 Understand the clustering approach to Data Analytics
Bloom’s: Analyze
AACSB: Reflective Thinking
AICPA: BB Industry; BB Leveraging Technology; FN Decision
Making
54) Assume that you will be up for a promotion next month and
you’d like to impress your boss with your data analytic skills. The company you
work for normally books the current month’s bad debit for the same amount as
the prior month’s actual accounts receivable write-offs. Using your general
accounting knowledge, explain why this process is not the best method. Next,
assuming that you will use a regression analysis, explain the process and
describe the data/information you would request/include to perform the
analysis.
Answer: Answers may vary!
1. GAAP
states that the allowance must still be established in the same accounting
period as the sale but is based on an anticipated and estimated figure. Using
the prior month’s actual write-offs does not follow the matching principal.
Also, this method does not account for year-to-year or month-to-month
fluctuation.
2. Regression
analysis involves the following process:
3. Identify
the variables that might predict an outcome.
4. Independent
variables: Current AR aging, Customer payment history, Collections success,
Current month’s sales
5. Determine
the functional form of the relationship.
6. Produce
a scatter plot of sales to actual write-offs over time to determine the prior
relationship, which can be used to estimate current and future relationships.
7. Identify
the parameters of the model.
8. Identify
the relative weights of each variable
9. Identify
the tables that contain the information you need. You can do this by looking
through the data dictionary or the relationship model.
Difficulty: 3 Hard
Topic: Regression Data Approach
Learning Objective: 03-04 Understand the regression and
classification approach to Data Analytics.
Bloom’s: Evaluate
AACSB: Reflective Thinking
AICPA: BB Industry; BB Leveraging Technology; FN Decision
Making
55) Benford’s Law (be sure to answer all 3 parts):
Part A: Briefly describe Benford’s Law.
Part B: Draw a graph that exemplifies data which conforms to
Benford’s Law (i.e., what it should look like).
Part C: Briefly describe how auditors could utilize Benford’s
Law while conducting testwork.
Answer: Answers will vary!
Part A:
- The
law states that in many naturally occurring collections of numbers, the
leading significant digit is likely to be small. For example, in sets that
obey the law, the number 1 appears as the most significant digit about 30%
of the time, while 9 appears as the most significant digit less than 5% of
the time.
- The
real world is more likely to have a low number as the first digit (e.g., 1
or 2) than a high number (e.g., 8 or 9). Benford used this realization to
predict the likelihood of digit frequencies across a wide variety of data,
including financial data
Part B:
Part C:
- Benford’s
Law can help identify unusual accounting activity.
- Auditors
can compare the frequency of digits predicted by Benford’s Law to the
actual frequency in a data file. Any category of numbers outside of
expectations (with a margin for error) should be investigated further.
Difficulty: 3 Hard
Topic: Example of Profiling in Auditing and Continuous
Auditing
Learning Objective: 03-02 Explain the profiling approach
to Data Analytics.
Bloom’s: Apply
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
Data Analytics for Accounting, 1e (Richardson)
Chapter 5 The Modern Audit and Continuous Auditing
1) A flat file is a single table of data with user-defined
attributes.
Answer: TRUE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
2) Heterogeneous systems represent one single installation or
instance of a system.
Answer: FALSE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
3) Production systems are those active systems that collect,
report, and are directly affected by current transactions.
Answer: TRUE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
4) Systems translator software maps the various tables and
fields from varied ERP systems into a consistent format.
Answer: TRUE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Understand
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology
5) Heterogeneous systems represent multiple installations or
instances of a system.
Answer: TRUE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
6) A data warehouse is a repository of data, including financial
data, accumulated from internal and external data sources, to help management
decision making.
Answer: TRUE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
7) The Audit Data Standards define common tables and fields that
are needed by auditors to perform common audit tasks. The Securities and
Exchange Commission, or SEC, developed these standards.
Answer: FALSE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
8) A flat file is a double table of data with user-defined
attributes.
Answer: FALSE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
9) Production systems are those active systems that collect,
report, and are directly affected by future transactions.
Answer: FALSE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
10) Systems translator software maps the various tables and
fields from varied EMR systems into a consistent format.
Answer: FALSE
Difficulty: 1 Easy
Topic: Auditing Data
Learning Objective: 05-02 Evaluate an Audit Plan
Bloom’s: Remember
AACSB: Reflective Thinking
AICPA: BB Leveraging Technology; FN Leveraging Technology;
FN Decision Making
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