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Solution Manual For Data Analytics for Accounting, 3rd Edition Richardson

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Solution Manual For Data Analytics for Accounting, 3rd Edition Richardson Chapter 1-9 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

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Data Analytics For Accounting
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Data Analytics For Accounting

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SOLUTIONMANUAL |




DataAnalyticsforAccounting, 3rd Edition
| | | | |




by Vernon Richardson,Chapters 1 - 9
| | | | | |




1

,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 | ofclasses |(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 | knownabout |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

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Data Analytics For Accounting
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Data Analytics For Accounting

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Subido en
19 de septiembre de 2025
Número de páginas
32
Escrito en
2025/2026
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