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Data Analytics for Accounting, 3rd Edition – Vernon Richardson | Solutions & Instructor’s Manual | Chapters 1–11 Complete Exam and Practice Support

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This document provides the complete solutions and instructor’s manual for Data Analytics for Accounting, 3rd Edition by Vernon Richardson, covering all chapters 1 through 11. It includes verified, accurate solutions designed to support coursework, assignments, case analyses, and exam preparation for accounting and data analytics students. The material aligns closely with the textbook structure and learning objectives, making it suitable for both guided instruction and independent study.

Voorbeeld van de inhoud

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SOLUTION & INSTRUCTOR’S MANUAL




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- Data Analytics for Accounting, 3rd Edition




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by Vernon Richardson




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CHAPTER 1-11| VERIFIED ACCURATE SOLUTIONS




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Chapter 1: Data Analytics for Accounting and Identifying the Questions




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Solutions to Multiple Choice Questions
1. (LO 1-1) Big Data is often described by the four Vs, or




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a. volume, velocity, veracity, and variability.




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b. volume, velocity, veracity, and variety.

c. volume, volatility, veracity, and variability.

d. variability, velocity, veracity, and variety.

Solution: 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

Solution: d



3. (LO 1-4) Which data approach attempts to identify similar individuals based on data known about them?

a. Classification

b. Regression

c. Similarity matching

d. Data reduction

Solution: 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

Solution: c

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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?




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a. Big Data

b. Data warehouse




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c. Data dictionary

d. Data Analytics

Solution: 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

Solution: 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

Solution: 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.

Solution: b



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9. (LO 1-4) The IMPACT cycle specifically includes all except the following steps:




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a. data preparation.

b. communicate insights.




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c. address and refine results.




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d. perform test plan.

Solution: a



10. LO 1-1) By the year 2024, the volume of data created, captured, copied, and consumed worldwide will be
149 .

a. zettabytes

b. petabytes

c. exabytes

d. yottabytes

Solution: a



Solutions to Discussion and Analysis Questions

1. The accounting function is one of being an information provider. To the extent that data is available to
address accounting questions, be they tax, managerial, audit or financial questions. With such rich available
data, and software tools to prepare and analyze the data, data analytics will continue to be an important tool for
accountants to use.

2. Data analytics is defined as the process of evaluating data with the purpose of drawing conclusions to
address business questions. Indeed, effective Data Analytics provides a way to search through large structured
and unstructured data to identify unknown patterns or relationships.

A university might learn from the analyzing the demographics of its current set of students in order to attract
its future student recruits. Did they come from cities or high schools that were close by? Were their parents
alumni of the university? Did they score high on certain parts of the ACT? Were those offered a scholarship
more likely to attend, etc.? Was social media effective in attracting new, potentially stronger students? By
analyzing this type of data, previously unknown patterns will emerge that will make recruiting students more
effective.

3. There are many potential answers. For example, Monsanto may use mathematical and statistical models to
plot out the best times to plant both male and female plants and where to plant them to maximize yield.
(https://www.cio.com/article/3221621/analytics/6-data- analytics-success-stories-an-inside-
look.html#tk.cio_rs)

4. There are many potential answers. Data analytics gives both internal and external auditors additional tools
to examine every accounting transaction and assess for compliance with GAAP. The audit process is changing
from a traditional process toward a more automated one, which will allow audit professionals to focus more on
the logic and rationale behind data queries and less on the gathering of the actual data. No longer will they be


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