SOLUTION MANUAL for Data Analytics for
Accounting, 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 cattempts cto cassign ceach cunit cin ca cpopulation cinto ca csmall cset cof
cclasses c(or cgroups) cwhere cthe cunit cbest cfits?
a. Regression
b. Similarity cmatching
c. Co-occurrence cgrouping
d. Classification
Answer: cd
3. (LO c1-4) cWhich cdata capproach cattempts cto cidentify csimilar cindividuals cbased con cdata cknown
cabout cthem?
a. Classification
b. Regression
c. Similarity cmatching
d. Data creduction
Answer: cc
4. (LO c1-4) cWhich cdata capproach cattempts cto cpredict cconnections cbetween ctwo cdata citems?
a. Profiling
b. Classification
c. Link cprediction
d. Regression
3
, Answer: cc
5. (LO c1-6) cWhich cof cthese cterms cis cdefined cas cbeing ca ccentral crepository cof cdescriptions cfor call cof
cthe cdata cattributes cof cthe cdataset?
a. Big cData
b. Data cwarehouse
c. Data cdictionary
d. Data cAnalytics
Answer: cc
6. (LO c1-5) cWhich cskills cwere cnot cemphasized cthat canalytic-minded caccountants cshould chave?
a. Developed can canalytics cmindset
b. Data cscrubbing cand cdata cpreparation
c. Classification cof ctest capproaches
d. Statistical cdata canalysis ccompetency
Answer: cc
7. (LO c1-5) cIn cwhich careas cwere cskills cnot cemphasized cfor canalytic-minded caccountants?
a. Data cquality
b. Descriptive cdata canalysis
c. Data cvisualization cand cdata creporting
d. Data cand csystems canalysis cand cdesign
Answer: cd
8. (LO c1-4) cThe cIMPACT ccycle cincludes call cexcept cthe cfollowing csteps:
a. perform ctest cplan.
b. visualize cthe cdata.
c. master cthe cdata.
d. track coutcomes.
Answer: cb
9. (LO c1-4) cThe cIMPACT ccycle cspecifically cincludes call cexcept cthe cfollowing csteps:
a. data cpreparation.
b. communicate cinsights.
c. address cand crefine cresults.
d. perform ctest cplan.
4
Accounting, 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 cattempts cto cassign ceach cunit cin ca cpopulation cinto ca csmall cset cof
cclasses c(or cgroups) cwhere cthe cunit cbest cfits?
a. Regression
b. Similarity cmatching
c. Co-occurrence cgrouping
d. Classification
Answer: cd
3. (LO c1-4) cWhich cdata capproach cattempts cto cidentify csimilar cindividuals cbased con cdata cknown
cabout cthem?
a. Classification
b. Regression
c. Similarity cmatching
d. Data creduction
Answer: cc
4. (LO c1-4) cWhich cdata capproach cattempts cto cpredict cconnections cbetween ctwo cdata citems?
a. Profiling
b. Classification
c. Link cprediction
d. Regression
3
, Answer: cc
5. (LO c1-6) cWhich cof cthese cterms cis cdefined cas cbeing ca ccentral crepository cof cdescriptions cfor call cof
cthe cdata cattributes cof cthe cdataset?
a. Big cData
b. Data cwarehouse
c. Data cdictionary
d. Data cAnalytics
Answer: cc
6. (LO c1-5) cWhich cskills cwere cnot cemphasized cthat canalytic-minded caccountants cshould chave?
a. Developed can canalytics cmindset
b. Data cscrubbing cand cdata cpreparation
c. Classification cof ctest capproaches
d. Statistical cdata canalysis ccompetency
Answer: cc
7. (LO c1-5) cIn cwhich careas cwere cskills cnot cemphasized cfor canalytic-minded caccountants?
a. Data cquality
b. Descriptive cdata canalysis
c. Data cvisualization cand cdata creporting
d. Data cand csystems canalysis cand cdesign
Answer: cd
8. (LO c1-4) cThe cIMPACT ccycle cincludes call cexcept cthe cfollowing csteps:
a. perform ctest cplan.
b. visualize cthe cdata.
c. master cthe cdata.
d. track coutcomes.
Answer: cb
9. (LO c1-4) cThe cIMPACT ccycle cspecifically cincludes call cexcept cthe cfollowing csteps:
a. data cpreparation.
b. communicate cinsights.
c. address cand crefine cresults.
d. perform ctest cplan.
4
