Test Bank for Introduction to Data Analytics for Accounting, 2nd Edition by Vernon Richardson
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Course
Advanced Accounting
Institution
Advanced Accounting
Test Bank for Introduction to Data Analytics for Accounting, 2nd Edition 2e by Vernon Richardson, Katie Terrell and Ryan Teeter. ISBN-13: 5141 Chapter 1 Ask the Question: Using Data Analytics to Address Accounting Questions Chapter 2 Master the Data: An Introduction to Accounting Data Chapter 3 Mas...
,ACCESS Test Bank for Introduction to Data Analytics for Accounting 2ndEdition Richardson
Richardson, Terrell, Teeter – Introduction to Data Analytics for Accounting, 2nd Edition – Chapter 1
Chapter 1 End-of-Chapter Assignment Solutions
Multiple Choice Questions
1. (LO 1-2) Which is the lowest level of critical thinking skills in Bloom’s Taxonomy?
a. Create
b. Remember
c. Apply
d. Analyze
2. (LO 1-2) Which is the highest level of critical thinking skills in Bloom’s Taxonomy?
a. Create
b. Apply
c. Analyze
d. Understand
3. (LO 1-2) Which is the appropriate ordering of critical thinking skills in Bloom’sTaxonomy, where the
“>” symbol means higher order skills?
a. Remember > Apply
b. Apply > Analyze
c. Analyze > Evaluate
d. Create > Analyze
4. (LO 1-3) Which step of the AMPS model most appropriately addresses the axiom,
“Your data won’t speak unless you ask it the right data analytics questions”?
a. Ask the Question
b. Master the Data
c. Perform the Analysis
d. Share the Story
5. (LO 1-3) Which step of the AMPS model most appropriately addresses the questionof the best way to
communicate data analytics findings with a decision maker?
a. Ask the Question
b. Master the Data
c. Perform the Analysis
d. Share the Story
6. (LO 1-3) What type of question is predicting whether a company will go bankrupt inthe coming two years?
a. What happened? What is happening?
b. Why did it happen? What are the root causes of past results?
c. Will it happen in the future? What is the probability something willhappen? Is it
forecastable?
,ACCESS Test Bank for Introduction to Data Analytics for Accounting 2ndEdition Richardson
Richardson, Terrell, Teeter – Introduction to Data Analytics for Accounting, 2nd Edition – Chapter 1
d. What should we do based on what we expect will happen? How do we
optimize our performance based on potential constraints?”
7. (LO 1-3) What type of question is choosing to take certain tax deductions based onthe way managers
believe tax legislation will change in the near future?
a. What happened? What is happening?
b. Why did it happen? What are the root causes of past results?
c. Will it happen in the future? What is the probability something will happen?Is it forecastable?
d. What should we do based on what we expect will happen? How do we
optimize our performance based on potential constraints?”
8. (LO 1-3) What type of question is finding the detail to more clearly understand whynet income is decreasing
when revenues are increasing?
a. What happened? What is happening?
b. Why did it happen? What are the root causes of past results?
c. Will it happen in the future? What is the probability something will happen?Is it forecastable?
d. What should we do based on what we expect will happen? How do we
optimize our performance based on potential constraints?”
9. (LO 1-4) What visualization type is most appropriate for evaluating the relationshipsbetween values?
a. Bar chart
b. Pie chart
c. Histogram
d. Scatterplot
10. (LO 1-5) Which of the following software tools specialize in data visualizations?
a. SPSS and Power Query
b. Alteryx and Tableau Prep
c. Power BI and Tableau
d. R and Python
Discussion Questions
1. (LO 1-1) The computer is better at automated, repetitive tasks since it can be programmed. The
computer is also not subject to fatigue and can process massive amounts of data easier than a
human can. Most of the value-added tasks and higher order thinking skills, such as analyzing,
evaluating and creating, are performed better by human accountants because they are not easily
programmed by a set of fixed rules. The ability
, ACCESS Test Bank for Introduction to Data Analytics for Accounting 2ndEdition Richardson
Richardson, Terrell, Teeter – Introduction to Data Analytics for Accounting, 2nd Edition – Chapter 1
to recognize tradeoffs, evaluating alternatives, and evaluating ad hoc factsare all better performed
by humans.
2. (LO 1-2) The skills taught in the introduction to financial accounting were the lower order
thinking skills (noted in Bloom’s Taxonomy) such as remembering, understanding and applying.
Application of journal entries,computing trial balances, recording transactions, bank
reconciliation, etc. are all examples of lower order skills.
3. (LO 1-3) Accountants understand the tradeoffs between relevant data and reliable data (such as
that data which might exhibit more representationalfaithfulness).
Accountants also understand the tradeoffs between unstructured and structured data, data internal
or external to the company, and even thepotential cost of acquiring and processing the data as
compared to the potential value provided by use of the data.
4. (LO 1-3) Mastering the data includes accessing, cleaning, and transformingthe data to prepare
the data for analysis.
5. (LO 1-3) Data analytics might be viewed as successively peeling the layer of an onion. By peeling the
first layer of the onion, you now are able to see thenext layer and evaluate it and remove it to get to
the third layer, etc. Often times, the AMPS model must be performed multiple times, refining the
question (Ask the Question), possibly considering different types of data (Master the Data),
performing additional analysis (Perform the Analysis) andretelling the story in each iteration
(Sharing the Story) before the issue/problem/challenge can be finally addressed with some
confidence.
6. (LO 1-3) Descriptive analysis reports what happened. Generally, evaluating the revenues and
earnings performance starts with descriptive analysis and continues with diagnostic analysis to
understand “Why it happened?”.
7. (LO 1-4, LO 1-5) Data acquisition and preparation software tools like SQL and Alteryx work to get
the data ready for analysis. Data visualization software tools work to both analyze data (as part
of "Perform the Analysis"in the AMPS model) and to communicate results (as part of "Share the
Story" in the AMPS model).
Brief Exercises
1. (LO1-1, LO1-2): Match the data analytics term to its data analytics definition:
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