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business
data analytics accounting

Questions and Answers of Data Analytics Accounting

For each of your questions, identify the account or data attribute you need to answer your question. Then use FASB’s XBRL taxonomy to identify the specific XBRL tags that represent those accounts.
Evaluate each question from Part 1.There are specific data attributes that will help you find the answer you’re looking for. For example, if your question was “Has[Company X’s] gross margin
Next to each question generate a hypothetical answer to the question to help you identify what your expected output would be. You may use some insight or intuition or search for industry averages to
Use what you know about financial statement analysis(or search the web if you need a refresher) to generate three different metrics for evaluating financial performance. For example, if you wanted to
Compare and Contrast: If you completed both tracks in this lab, which tool are you most interested in learning and why? (This question does not appear in Connect. Write your response in your lab
What type of computer operating system do you normally use? (Answer this in Connect or write your response in your lab document.)
Where did you go to complete this lab activity?(Answer this in Connect or write your response in your lab document.)
What is the purpose of taking screenshots of your progress through the labs? (Answer this in Connect or write your response in your lab document.)
Where should you answer objective lab questions? (Answer this in Connect or write your response in your lab document.)
According to your instructor, which track(s) will you be completing this semester? (Answer this in Connect or write your response in your lab document.)
(LO 1-6) Consider the 2013 rejected loan data from LendingClub titled “DAA Chapter 1-2 Data.” Browse the file in Excel to ensure there are no missing data.Because our analysis requires risk
(LO 1-6) Consider the 2013 rejected loan data from LendingClub titled “DAA Chapter 1-2 Data.” Browse the file in Excel to ensure there are no missing data.Because our analysis requires risk
(LO 1-6) Consider the 2013 rejected loan data from LendingClub titled “DAA Chapter 1-2 Data” from Connect Additional Student Resources. Browse the file in Excel to ensure there are no missing
Analysis: Does each state’s loan rejection percentage roughly correspond to its relative proportion of the U.S. population (by 2010 U.S. census at
What is the state with the lowest percentage of rejected loans?
What is the state with the highest percentage of rejected loans?
Put the following states in order of their loan rejection percentage based on the count of rejected loans (from high [1] to low [11]) of the total rejected loans.Does each state’s loan rejection
Multiple Choice: Is this loan rejection percentage greater than the percentage of the U.S. population that lives in Arkansas (per 2010 census)?a. Loan rejection percentage is greater than the
Multiple Choice: What is the percentage of total loans rejected in the United States that came from Arkansas?a. Less than 1%.b. Between 1% and 2%.c. More than 2%.Navigate to the Connect Additional
(LO 1-6) Navigate to the Connect Additional Student Resources page. Under Chapter 1 Data Files, download and consider the rejected loans dataset of LendingClub data titled “DAA Chapter 1-1 Data.”
(LO 1-6) Navigate to the Connect Additional Student Resources page. Under Chapter 1 Data Files, download and consider the LendingClub data dictionary file“LCDataDictionary,” specifically the
(LO 1-5) Match the specific analysis need/characteristic to the appropriate Tableau Track software tool:Tableau Prep Builder Tableau Desktop Tableau Public Specific Analysis Need/Characteristic 1.
(LO 1-5) Match the specific analysis need/characteristic to the appropriate Microsoft Track software tool:Excel Power Query Power BI Power Automate Specific Analysis Need/Characteristic 1. Basic
(LO 1-4) Match each of the specific Data Analytics tasks to the stage of the IMPACT cycle:Identify the Questions Master the Data Perform Test Plan Address and Refine Results Communicate Insights
(LO 1-4) Match each specific Data Analytics test to a specific test approach, as part of performing a test plan:Classification Regression Similarity Matching Clustering Co-occurrence Grouping
(LO 1-6) 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)
(LO 1-6) Why might the debt-to-income attribute included in the declined loans dataset considered in the chapter be a predictor of declined loans? How about the credit (risk) score?
(LO 1-4) Which data approach might be used to assess the appropriate level of the allowance for doubtful accounts?
(LO 1-4) Auditors will frequently use the data reduction approach when considering potentially risky transactions. Provide an example of why focusing on a portion of the total number of transactions
(LO 1-4) What data approach mentioned in the chapter might be used by Facebook to find friends?
(LO 1-4) What is included in mastering the data as part of the IMPACT cycle described in the chapter?
(LO 1-4) Why is identifying the question such a critical first step in the IMPACT process cycle?
(LO 1-4) Describe the IMPACT cycle. Why does its order of the processes and its recursive nature make sense?
(LO 1-3) How is the role of management accounting similar to the role of the data analyst?
(LO 1-3) How might Data Analytics be used in financial reporting? And how might it be used in doing tax planning?
(LO 1-3) Give a specific example of how Data Analytics creates value for auditing.
(LO 1-2) Give a specific example of how Data Analytics creates value for businesses.
(LO 1-1) Define Data Analytics and explain how a university might use its techniques to recruit and attract potential students.
(LO 1-1) The opening article “Accountants to Rely More on Big Data in 2020”suggested that Data Analytics would be increasingly implementing Big Data in their business processes. Why is that? How
(LO 1-1) By the year 2024, the volume of data created, captured, copied, and consumed worldwide will be 149 _____.a. zettabytesb. petabytesc. exabytesd. yottabytes
(LO 1-4) The IMPACT cycle specifically includes all except the following steps:a. data preparation.b. communicate insights.c. address and refine results.d. perform test plan.
(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.
(LO 1-5) In which areas were skills not emphasized for analytic-minded accountants?a. Data qualityb. Descriptive data analysisc. Data visualization and data reportingd. Data and systems analysis and
(LO 1-5) Which skills were not emphasized that analytic-minded accountants should have?a. Developed an analytics mindsetb. Data scrubbing and data preparationc. Classification of test approachesd.
(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?a. Big Datab. Data warehousec. Data dictionaryd. Data Analytics
(LO 1-4) Which data approach attempts to predict connections between two data items?a. Profilingb. Classificationc. Link predictiond. Regression
(LO 1-4) Which data approach attempts to identify similar individuals based on data known about them?a. Classificationb. Regressionc. Similarity matchingd. Data reduction
(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. Regressionb. Similarity matchingc. Co-occurrence
(LO 1-1) Big Data is often described by the four Vs, ora. volume, velocity, veracity, and variability.b. volume, velocity, veracity, and variety.c. volume, volatility, veracity, and variability.d.
Performing your own analysis, download the rejected loans dataset titled “DAA Chapter 1-1 Data” and run an Excel PivotTable by risk (or credit) score classification and DTI bucket to determine
Performing your own analysis, download the rejected loans dataset titled “DAA Chapter 1-1 Data” and perform an Excel PivotTable analysis by state (including the District of Columbia) and figure
Lenders often use the data item of whether a potential borrower rents or owns their house. Beyond the three characteristics of rejected loans analyzed in this section, do you believe this data item
Stated specifically, our question is, “What are some characteristics of rejected loans?”
Why is having the Tableau software tools fully available on both Windows and Mac computers an advantage for Tableau over Microsoft?
Given the “magic quadrant” in Exhibit 1-4, why are the software tools represented by the Microsoft and Tableau tracks considered innovative?
How might a data reduction approach be used in auditing to allow the auditor to spend more time and effort on the most important (e.g., most risky, largest dollar volume, etc.) items?
Let’s say we are trying to predict how much money college students spend on fast food each week. What would be the response, or dependent, variable?What would be examples of independent variables?
How specifically will Data Analytics change the way a tax staff does its taxes?
Why are management accounting and Data Analytics considered similar in many respects?
How might Data Analytics assess the decision to either grant overtime to current employees or hire additional employees? Specifically, consider how Data Analytics might be helpful in reducing a
Let’s assume a brand manager at Procter and Gamble identifies that an older demographic might be concerned with the use of Tide Pods to do their laundry.How might Procter and Gamble use Data
Banks know a lot about us, but they have traditionally used externally generated credit scores to assess creditworthiness when deciding whether to extend a loan. How would you suggest a bank use Data
How does having more data around us translate into value for a company?What must we do with those data to extract value?
Explain how the IMPACT model may be used to address a specific business question.
Describe the skills needed by accountants.
Describe the Data Analytics Process using the IMPACT cycle.
Explain why Data Analytics matters to accountants.
Understand why Data Analytics matters to business.
(LO 7-1, LO 7-2) Match the diagnostic analytics term to its definition. Diagnostic Analytics Term Variance analysis Anomaly Sequence check Diagnostic analytics Descriptive analytics Diagnostic
(LO 7-2, LO 7-3) Match the diagnostic analytics to an example or definition. Diagnostic Analytics Sunk cost fallacy Sequence check Two-sample t-test difference of means Variance analysis Outlier
(LO 7-2, LO 7-3) Match the diagnostic analytics to the appropriate example or definition. Diagnostic Analytics Separation of duties Management by exception Two-sample t-test difference of means
(LO 7-2) Which party needs to adjust its cash balance once learning about the following reconciling items? Reconciling Item Error Outstanding check NSF check Outstanding deposit Notes/interest
(LO 7-2, LO 7-3) Name the appropriate diagnostic analytics technique utilized to find each type of anomaly. Choose from regression analysis, drill-down detail, Benford’s law, duplicate check, and
(LO 7-2) For which of the various potential transactions would analysis using Benford’s law be useful to perform? Transactions $500 is the minimum refund ATM withdrawals are in $20 denominations
(LO 7-2) The equation log10(1 + (1/d)), where d is each digit 1, 2, and so on, gives the expectation of the frequency of Benford’s law for each digit.Required:1. Calculate the expected distribution
(LO 7-2) Download the “Population of Countries of the World” dataset in Excel from Connect (Dataset original source accessed May 2020:
(LO 7-3) Download the “R&D Expenditures and Revenues” dataset in Excel from Connect. Assess the relationship between R&D Expenditures and Sales Revenue by computing correlations and visualizing
(LO 7-3) Download the “R&D Expenditures and Revenues” dataset in Power BI or Tableau from Connect. Assess the relationship between R&D Expenditures and Sales Revenue by creating scatterplots and
(LO 7-3) Download the “R&D Expenditures and Revenues” dataset from Connect into your preferred software tool. Assess the relationship between R&D Expenditures and Revenue by performing a
(LO 8-2) Which predictive analytics technique would be used to predict whether a firm is likely to go bankrupt in the coming year?a. Regressionb. Classificationc. Benford’s lawd. Monetary unit
(LO 8-2, LO 8-3) Which predictive analytics technique would be used to predict the interest rate given from a lender (bank) to a borrower?a. Regressionb. Classificationc. Benford’s lawd. Monetary
(LO 8-2) Would a greater amount of working capital/total assets lead to more bankrupt or less bankrupt firms?a. More bankruptb. Less bankrupt
(LO 8-2) If a company has an Altman Z-score of 2.8, the company would be classified in the .a. distress zone, or at significant risk of bankruptcyb. gray zone, or at risk of
(LO 8-5) According to the text, prefers -basis accounting since it is better at forecasting future performance.a. GAAP, cashb. GAAP, accrualc. tax accounting,
(LO 8-5) Which is more persistent in predicting future amounts of the variable based on current amounts of that same variable?a. Cash flows from operating activitiesb. Cash flows from investment
(LO 8-5) The persistence of as compared to is consistent with GAAP requiring the use of accrual accounting for financial reporting purposes.a. sales; operating
(LO 8-2) Predicting which companies are likely to be fraudulent/not fraudulent or likely to be bankrupt or not bankrupt are examples of .a. classificationb. predictionc.
(LO 8-2) All of the following are factors used by Altman’s Z in predicting bankruptcy except:a. Sales/Total assetsb. Market value of stockholders’ equity/Book value of total debt owedc. Retained
(LO 8-2) According to Beneish, which of the following factors are predictive of financial statement fraud?a. Sales/Total assetsb. Market value of stockholders’ equity/Book value of total debt
(LO 8-5) Predicting future operating income would be an example of which type of predictive analytics?a. Time seriesb. Regressionc. Classification
(LO 8-7) A software program that automates certain repeatable tasks is called .a. machine learningb. automated task repetitionc. robotic process automationd. predictive automation
(LO 8-2) Classification analysis to decide on client acceptance or rejection is most important for .a. lendersb. auditorsc. audit regulatorsd. investors
(LO 8-4) Not considering historical averages when making predictions of possible future events is known as .a. base rate fallacyb. base rate ignorancec. historical rate fallacyd.
(LO 8-2) Predictive analytics technique to separate a sample (or population) into one or more groups or classes is called .a. regressionb. classificationc. time seriesd. forecasting
(LO 8-1) How is predictive analytics different from descriptive or diagnostic analytics?
(LO 8-2) How does Altman’s Z work in predicting bankruptcy? How could we test it to see if it still makes good predictions today?
(LO 8-2) Why is a potential borrower’s employment history an important component of determining whether to extend a loan?
(LO 8-2, LO 8-3) Why are credit history and credit score good predictors of the appropriate interest rate to be offered to a borrower?
(LO 8-2, LO 8-3) How is predicting what interest rate Lending Club will give its customers a regression exercise, as opposed to a classification activity?
(LO 8-2) Why is deciding to resign from a potentially risky audit client an important decision for an auditor?

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