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Test Bank For Data Analytics for Accounting 3rd Edition By Vernom Richardson, Complete All Chapters - Newest Version (2024/2025)

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Test Bank For Data Analytics for Accounting 3rd Edition By Vernom Richardson, Complete All Chapters | Newest Version 2024/2025.Chapter 01: Student name:__________ 1) Data analytics is the process of evaluating data with the purpose of drawing conclusions to address 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 their businesses, 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 and compare this to inventory obsolescence and other estimates. ⊚ true ⊚ false 5) Data analytics allows auditors to glean insights that are beneficial to the client, without breeching independence. ⊚ true ⊚ false 6) The predictive analytics is an important aspect of data analytics for auditors, but is not applicable 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 new questions are identified. ⊚ true ⊚ false 14) Data analysis through data manipulation is performing basic analysis to understand the quality 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 how data analytics can address business questions. ⊚ true ⊚ false 17) While it is important for accountants to clearly articulate the business problem, drawing appropriate 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 each varied decision maker and their specific needs. ⊚ true ⊚ false 19) With a goal to give organizations the information they need to make sound and timely business 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 risks and 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 ability to address the business question C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows 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 ability to address the business question C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows 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 ability to address the business question C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows 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 ability to address the business question C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that allows 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 ability to 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 ability to 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 their specific needs 31) Which of the following best describes the goal of defining and addressing problems through statistical 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 ability to address the business question C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that allows enhanced analysis D) identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis 32) While accountants don't need to become data scientists, they must know how to do the following except: A) Clearly articulate the business problem the company is facing B) Communicate with the data scientists about specific data needs and understand the underlying 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 time cleaning 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 numerical value 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 an individual, 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 would arguably 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 to be 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 transactions involving 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 transactions involving 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 transactions involving them.


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Vernon J. Richardson, Ryan Teeter, Katie L. Terrell Data Analytics for Accounting
Publisher: 2019 ISBN: 9781260571097 Edition: Unknown

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