SOLUTION MANUAL for Data Analytics for Accounting,
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| 3rd Edition by Vernon Richardson, Chapters 1 - 9
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1
,TABLE OF CONTENTS
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Chapter 1: Data Analytics for Accounting and Identifying the Questions
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Chapter 2: Mastering the Data
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Chapter 3: Performing the Test Plan and Analyzing the Results
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Chapter 4: Communicating Results and Visualizations
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Chapter 5: The Modern Accounting Environment
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Chapter 6: Audit Data Analytics
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Chapter 7: Managerial Analytics
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Chapter 8: Financial Statement Analytics
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Chapter 9: Tax Analytics
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2
,Solutions Manual – Chapter 1
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Solutions |to |Multiple |Choice |Questions
1. (LO |1-1) |Big |Data |is |often |described |by |the |four |Vs, |or
a. volume, |velocity, |veracity, |and |variability.
b. volume, |velocity, |veracity, |and |variety.
c. volume, |volatility, |veracity, |and |variability.
d. variability, |velocity, |veracity, |and |variety.
Answer: |b
2. LO |1-4) |Which |data |approach |attempts |to |assign |each |unit |in |a |population |into |a |small |set |of|classes
|(or |groups) |where |the |unit |best |fits?
a. Regression
b. Similarity |matching
c. Co-occurrence |grouping
d. Classification
Answer: |d
3. (LO |1-4) |Which |data |approach |attempts |to |identify |similar |individuals |based |on |data |known|about
|them?
a. Classification
b. Regression
c. Similarity |matching
d. Data |reduction
Answer: |c
4. (LO |1-4) |Which |data |approach |attempts |to |predict |connections |between |two |data |items?
a. Profiling
b. Classification
c. Link |prediction
d. Regression
3
, Answer: |c
5. (LO |1-6) |Which |of |these |terms |is |defined |as |being |a |central |repository |of |descriptions |for |all |of|the
|data |attributes |of |the |dataset?
a. Big |Data
b. Data |warehouse
c. Data |dictionary
d. Data |Analytics
Answer: |c
6. (LO |1-5) |Which |skills |were |not |emphasized |that |analytic-minded |accountants |should |have?
a. Developed |an |analytics |mindset
b. Data |scrubbing |and |data |preparation
c. Classification |of |test |approaches
d. Statistical |data |analysis |competency
Answer: |c
7. (LO |1-5) |In |which |areas |were |skills |not |emphasized |for |analytic-minded |accountants?
a. Data |quality
b. Descriptive |data |analysis
c. Data |visualization |and |data |reporting
d. Data |and |systems |analysis |and |design
Answer: |d
8. (LO |1-4) |The |IMPACT |cycle |includes |all |except |the |following |steps:
a. perform |test |plan.
b. visualize |the |data.
c. master |the |data.
d. track |outcomes.
Answer: |b
9. (LO |1-4) |The |IMPACT |cycle |specifically |includes |all |except |the |following |steps:
a. data |preparation.
b. communicate |insights.
c. address |and |refine |results.
d. perform |test |plan.
4
| | | | | |
| 3rd Edition by Vernon Richardson, Chapters 1 - 9
| | | | | | | | |
1
,TABLE OF CONTENTS
| |
Chapter 1: Data Analytics for Accounting and Identifying the Questions
| | | | | | | | |
Chapter 2: Mastering the Data
| | | |
Chapter 3: Performing the Test Plan and Analyzing the Results
| | | | | | | | |
Chapter 4: Communicating Results and Visualizations
| | | | |
Chapter 5: The Modern Accounting Environment
| | | | |
Chapter 6: Audit Data Analytics
| | | |
Chapter 7: Managerial Analytics
| | |
Chapter 8: Financial Statement Analytics
| | | |
Chapter 9: Tax Analytics
| | |
2
,Solutions Manual – Chapter 1
| | | |
Solutions |to |Multiple |Choice |Questions
1. (LO |1-1) |Big |Data |is |often |described |by |the |four |Vs, |or
a. volume, |velocity, |veracity, |and |variability.
b. volume, |velocity, |veracity, |and |variety.
c. volume, |volatility, |veracity, |and |variability.
d. variability, |velocity, |veracity, |and |variety.
Answer: |b
2. LO |1-4) |Which |data |approach |attempts |to |assign |each |unit |in |a |population |into |a |small |set |of|classes
|(or |groups) |where |the |unit |best |fits?
a. Regression
b. Similarity |matching
c. Co-occurrence |grouping
d. Classification
Answer: |d
3. (LO |1-4) |Which |data |approach |attempts |to |identify |similar |individuals |based |on |data |known|about
|them?
a. Classification
b. Regression
c. Similarity |matching
d. Data |reduction
Answer: |c
4. (LO |1-4) |Which |data |approach |attempts |to |predict |connections |between |two |data |items?
a. Profiling
b. Classification
c. Link |prediction
d. Regression
3
, Answer: |c
5. (LO |1-6) |Which |of |these |terms |is |defined |as |being |a |central |repository |of |descriptions |for |all |of|the
|data |attributes |of |the |dataset?
a. Big |Data
b. Data |warehouse
c. Data |dictionary
d. Data |Analytics
Answer: |c
6. (LO |1-5) |Which |skills |were |not |emphasized |that |analytic-minded |accountants |should |have?
a. Developed |an |analytics |mindset
b. Data |scrubbing |and |data |preparation
c. Classification |of |test |approaches
d. Statistical |data |analysis |competency
Answer: |c
7. (LO |1-5) |In |which |areas |were |skills |not |emphasized |for |analytic-minded |accountants?
a. Data |quality
b. Descriptive |data |analysis
c. Data |visualization |and |data |reporting
d. Data |and |systems |analysis |and |design
Answer: |d
8. (LO |1-4) |The |IMPACT |cycle |includes |all |except |the |following |steps:
a. perform |test |plan.
b. visualize |the |data.
c. master |the |data.
d. track |outcomes.
Answer: |b
9. (LO |1-4) |The |IMPACT |cycle |specifically |includes |all |except |the |following |steps:
a. data |preparation.
b. communicate |insights.
c. address |and |refine |results.
d. perform |test |plan.
4
