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Data Analytics for Accounting
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Data Analytics for Accounting
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Solution Manual For Data Analytics for Accounting, 3rd Edition Richardson All Chapters Complete Fully Covered A+ Solutions ISBN:9781260571097 Newest 2024 Version
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Data Analytics for Accounting
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Data Analytics for Accounting
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SOLUTION MANUAL For Data Analytics for Accounting, 3rdEdition by Vernon Richardson, Verified Chapters 1 - 9,
Complete Newest Version
Which skills were not emphasized that analytic-minded accountants should have?
Multiple Choice
A. Statistical data analysis competency
B. Classification of test approaches
C. Developed an analytics mindset
D. Data scrubbing and data preparation - ANSWER: B. Classification of test
approaches
In which areas were skills not emphasized for analytic-minded accountants?
Multiple Choice
A. Descriptive data analysis
B. Data and systems analysis and design
C. Data visualization and data reporting
D. Data quality - ANSWER: B. Data and systems analysis and design
The IMPACT cycle includes all except the following steps:
Multiple Choice
A. perform test plan.
B. master the data.
C. track outcomes.
D. visualize the data. - ANSWER: D. visualize the data.
The IMPACT cycle specifically includes all except the following steps:
Multiple Choice
A. address and refine results.
B. perform test plan.
C. communicate insights.
D. data preparation. - ANSWER: D. data preparation.
Why is identifying the question such a critical first step in the IMPACT process cycle?
- ANSWER: Data analysis is most effective when a question is identified that needs to
be addressed. That will focus the analysis on which data and which test method
might be most effective in addressing or answering the question.
To address the question "Will I receive a loan from LendingClub?" we had available
data to assess the relationship among (1) the debt-to-income ratios and number of
rejected loans, (2) the length of employment and number of rejected loans, and (3)
the credit (or risk) score and number of rejected loans. What additional data would
, you recommend to further assess whether a loan would be offered? Why would they
be helpful? - ANSWER: There are many other potential predictors of whether the
LendingClub would pay a loan. Here are a few possibilities: What other debt do they
have? How much is their disposable income? Do they have a clean criminal record?
Have they had a loan with LendingClub before and did they repay it? Do they rent or
own their house?
What data analytics test will predict which firms will go bankrupt and which firms
will not go bankrupt? - ANSWER: Classification
What data analytics test will use stratified sampling to focus audit effort on
transactions with greatest risk.? - ANSWER: Data Reduction
What data analytics test will Work to understand normal behavior, to then be able to
identify abnormal behavior (such as fraud)? - ANSWER: Profilling
What data analytics test will look for relationships between related parties that are
not otherwise disclosed.? - ANSWER: Link Prediction
What data analytics test will predict which new customers resemble the company's
best customers? - ANSWER: Similarity Matching
What data analytics test will predict the relationship between an investment in
advertising expenditures and subsequent operating income? - ANSWER: Regression
What data analytics test will segment all of the company's customers into groups
that will allow further specific analysis? - ANSWER: Clustering
What data analytics test will identity customers who buy product X will be most
likely to be also interested in product Y. - ANSWER: Co-occurrence Grouping
Mastering the data can also be described via the ETL process. The ETL process stands
for: - ANSWER: extract, transform, and load data
Which of the following describes part of the goal of the ETL process?
Multiple Choice
A. Identify which approach to data analytics should be used.
B. Load the data into a relational database for storage.
C. Communicate the results and insights found through the analysis.
D. Identify and obtain the data needed for solving the problem. - ANSWER: D.
Identify and obtain the data needed for solving the problem.
The purpose of transforming data is:
A. to validate the data for completeness and integrity.
B. to load the data into the appropriate tool for analysis.
C. to obtain the data from the appropriate source.
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