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TEST BANK For Data Analytics for Accounting 3rd Edition by Richardson, Teeter & Terrell, Chapters 1 - 9, Complete Newest Version €17,65
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TEST BANK For Data Analytics for Accounting 3rd Edition by Richardson, Teeter & Terrell, Chapters 1 - 9, Complete Newest Version

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TEST BANK For Data Analytics for Accounting 3rd Edition by Richardson, Teeter & Terrell, Chapters 1 - 9, Complete Newest Version TEST BANK For Data Analytics for Accounting, 3rd Edition by Vernon Richardson, Verified Chapters 1 - 9, Complete Newest Version Chapter 1: Data Analytics for Accounti...

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  • 9 juni 2024
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  • data
  • analytics
  • accounting
  • richardson
  • 3rd edition
  • teeter
  • terrell
  • data analytics for accounting
  • data analytics for accounting 3rd edition
  • test bank

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Voorbeeld van de inhoud

TEST BANK
Data Analytics for Accounting, 3rd Edition
by Vernon Richardson, Chapters 1 – 9

,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

,Answers are at the End of Each Chapter

Chapter 01:
Student name:
1) Data analytics is the process of evaluating data with the purpose of drawing conclusions
toaddress business questions.
⊚ true
⊚ false



2) The process of data analytics aims to transform raw information into data to create value.
⊚ true
⊚ false



3) Data analytics has the potential to transform the manner in which companies run
theirbusinesses, however it is not practical in the near future.
⊚ true
⊚ false



4) Auditors can use social media to hear what customers are saying about a company
andcompare this to inventory obsolescence and other estimates.
⊚ true
⊚ false



5) Data analytics allows auditors to glean insights that are beneficial to the client,
withoutbreeching independence.
⊚ true
⊚ false

,6) The predictive analytics is an important aspect of data analytics for auditors, but is
notapplicable for tax accountants.
⊚ true
⊚ false



7) The I in IMPACT Cycle represents Identify the Question.
⊚ true
⊚ false



8) The M in IMPACT Cycle represents Master the Data.
⊚ true
⊚ false



9) The P in IMPACT Cycle represents Predict the Results.
⊚ true
⊚ false



10) The A in IMPACT Cycle represents Analyze the Data.
⊚ true
⊚ false



11) The C in IMPACT Cycle represents Continuously Track.
⊚ true
⊚ false



12) The T in IMPACT Cycle represents Track Outcomes.
⊚ true
⊚ false

,13) The IMPACT cycle is iterative, as insights are gained, outcomes are tracked, and
newquestions are identified.
⊚ true
⊚ false



14) Data analysis through data manipulation is performing basic analysis to understand
thequality of the underlying data and its ability to address the business question.
⊚ true
⊚ false



15) To be proficient in data analysis, accountants need to become data scientists.
⊚ true
⊚ false



16) By developing an analytics mindset, accountants will be able to recognize when and
howdata analytics can address business questions.
⊚ true
⊚ false



17) While it is important for accountants to clearly articulate the business problem,
drawingappropriate conclusions, based on the data, should be left to statisticians.
⊚ true
⊚ false



18) Analytic-minded accountants should report results of analysis in an accessible way to
eachvaried decision maker and their specific needs.
⊚ true
⊚ false

,19) With a goal to give organizations the information they need to make sound and
timelybusiness decisions, data analytics often involves all of the following except:
A) technologies.
B) statistics.
C) strategies.
D) databases.



20) Patterns discovered from enable businesses to identify opportunities and
risksand better plan for .
A) past archives; the future
B) current data; the future
C) current data; today
D) past archives; today



21) Which of the following best describes the goal of descriptive data analysis:
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner
thatallows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis



22) Which of the following Microsoft software tool specializes in data joining?
A) Excel
B) Power Query
C) Power BI
D) Power Automate



23) Which of the following Microsoft software tools specializes in creating dashboards?
A) Excel
B) Power Query
C) Power BI
D) Power Automate

,24) Which of the following Tableau software tools specializes in data transformation?
A) Tableau Desktop
B) Tableau Prep Builder
C) Tableau Public
D) Tableau Visualize



25) Which of the following Tableau software tools specializes in creating dashboards?
A) Tableau Desktop
B) Tableau Prep Builder
C) Tableau Public
D) Tableau Visualize



26) Which of the following best describes the goal of data quality:
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner
thatallows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis



27) Which of the following best describes the goal of data manipulation:
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner
thatallows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis



28) Which of the following best describes the goal of data scrubbing and data preparation:
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner
thatallows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis

,29) Which of the following best describes the goal of developing an analytics mindset:
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) comprehend the process needed to clean and prepare the data before analysis



30) Which of the following best describes the goal of data visualization and data reporting:
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) report results of analysis in an accessible way to each varied decision maker and
theirspecific needs



31) Which of the following best describes the goal of defining and addressing problems
throughstatistical data analysis:
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its
abilityto address the business question
C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner
thatallows enhanced analysis
D) identify and implement an approach that will use statistical data analysis to
drawconclusions and make recommendations on a timely basis



32) While accountants don't need to become data scientists, they must know how to do
thefollowing except:
A) Clearly articulate the business problem the company is facing
B) Communicate with the data scientists about specific data needs and understand
theunderlying quality of the data
C) Build a data repository
D) Comprehend the process needed to clean and prepare the data before analysis

,33) Data analytics professionals estimate that they spend between of their
timecleaning data so it can be analyzed.

A) 50 percent and 90 percent
B) 10 percent and 20 percent
C) 20 percent and 50 percent
D) 70 percent and 95 percent



34) Which approach to data analytics attempts to estimate or predict, for each unit, the
numericalvalue of some variable using some type of statistical model?
A) Similarity matching.
B) Classification.
C) Data reduction.
D) Regression.



35) Which approach to data analytics attempts to characterize the typical behavior of
anindividual, group or population by generating summary statistics about the
data?
A) Similarity matching.
B) Profiling.
C) Data reduction.
D) Regression.



36) Since some transactions need more attention than others, the data reduction approach
wouldarguably be most important for the function.

A) audit
B) tax.
C) management accounting.
D) Regression.

, 37) Which approach to data analytics attempts to reduce the amount of information that
needs tobe considered to focus on the most critical items?
A) Similarity matching.
B) Profiling.
C) Data reduction.
D) Regression.



38) Which of the following best describes the classification approach to data analytics?
A) An attempt to assign each unit (or individual) in a population into a few categories.
B) An attempt to identify similar individuals based on data known about them.
C) An attempt to divide individuals into groups in a useful or meaningful way.
D) An attempt to discover associations between individuals based on
transactionsinvolving them.



39) Which of the following best describes the clustering approach to data analytics?
A) An attempt to assign each unit (or individual) in a population into a few categories.
B) An attempt to identify similar individuals based on data known about them.
C) An attempt to divide individuals into groups in a useful or meaningful way.
D) An attempt to discover associations between individuals based on
transactionsinvolving them.



40) Which of the following best describes the similarity matching approach to data analytics?
A) An attempt to assign each unit (or individual) in a population into a few categories.
B) An attempt to identify similar individuals based on data known about them.
C) An attempt to divide individuals into groups in a useful or meaningful way.
D) An attempt to discover associations between individuals based on
transactionsinvolving them.



41) Which of the following best describes the regression approach to data analytics?
A) An attempt to estimate or predict, for each unit, the numerical value of some
variableusing some type of statistical model.
B) An attempt to predict a relationship between two data items.
C) An attempt to divide individuals into groups in a useful or meaningful way.
D) An attempt to discover associations between individuals based on
transactionsinvolving them.

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