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Which of the following best describes an unsupervised approach to the evaluation of data? a. Data exploration looking for potential patterns of interest b. Data exploration to examine the relationships between variables that are hypothesized to exist c. Data exploration that is conducted with direct oversight by a superior d. Data exploration that is free from oversight by a superior

a. Data exploration looking for potential patterns of interest

What are attributes that exist in a relational database that are neither primary nor foreign keys? a. Descriptive attributes b. Nondescript attributes c. Composite keys d. Relational table attributes

a. Descriptive attributes

The advantages of storing data in a relational database include which of the following? a. Help in enforcing business rules and integrating business processes. b. Integrating business processes. c. Increased information redundancy. d. Help in enforcing business rules.

a. Help in enforcing business rules and integrating business processes.

Which attribute is required to exist in each table of a relational database and serves as the "unique identifier" for each record in a table? a. Primary key b. Foreign key c. Key attribute d. Unique identifier

a. Primary key

Which of the following is the best choice as the unique identifier for each sales order? a. Sales_Order# b. Purchase_Order# c. Item# d. Shipping#

a. Sales_Order#

What allows tax departments to view multiple years, periods, jurisdictions (state or federal or international, etc.), and differing scenarios of data, typically through use of a dashboard? a. Tax data visualizations b. Tax data warehouses c. Tax planning d. Tax compliance data

a. Tax data visualizations

______ is a set of data used to assess the degree and strength of a predicted relationship. a. Test data b. Training data c. Structured data d. Unstructured data

a. Test data

According to the textbook, an example of a tax efficiency and effectiveness KPI would be: a. amount of time spent on compliance versus strategic activities. b. ETR (effective tax rate) over time. c. number of resubmitted tax returns due to errors. d. number of audits closed.

a. amount of time spent on compliance versus strategic activities.

The IMPACT cycle specifically includes all except the following steps: a. data preparation. b. communicate insights. c. perform test plan. d. address and refine results.

a. data preparation.

Mastering the data can also be described via the ETL process. The ETL process stands for: a. extract, transform, and load data. b. enter, transform, and load data. c. enter, total, and load data. d. extract, total, and load data.

a. extract, transform, and load data.

The Fahrenheit scale of temperature measurement would best be described as an example of: a. interval data. b. nominal data. c. continuous data. d. discrete data.

a. interval data.

In general, the more complex the model, the greater the chance of: a. overfitting the data. b. underfitting the data. c. pruning the data. d. a more accurate prediction of the data.

a. overfitting the data.

The task of tax accountants and tax departments to minimize the amount of taxes paid in the future is called: a. tax planning. b. tax compliance. c. tax sustainability. d. tax minimization.

a. tax planning.

The IMPACT cycle includes all except the following steps: a. visualize the data. b. perform test plan. c. master the data. d. track outcomes.

a. visualize the data.

Big Data is often described by the four Vs, or a. volume, velocity, veracity, and variety. b. volume, volatility, veracity, and variability. c. variability, velocity, veracity, and variety. d. volume, velocity, veracity, and variability.

a. volume, velocity, veracity, and variety.

Which approach to data analytics attempts to assign each unit in a population into a small set of classes where the unit belongs? a. Similarity matching b. Classification c. Co-occurrence grouping d. Regression

b. Classification

Which testing approach would be used to predict whether certain cases should be evaluated as having fraud or no fraud? a. Sentiment analysis b. Classification c. Probability d. Artificial intelligence

b. Classification

Which skills were not emphasized that analytic-minded accountants should have? a. Developed an analytics mindset b. Classification of test approaches c. Data scrubbing and data preparation d. Statistical data analysis competency

b. Classification of test approaches

In which areas were skills not emphasized for analytic-minded accountants? a. Descriptive data analysis b. Data and systems analysis and design c. Data quality d. Data visualization and data reporting

b. Data and systems analysis and design

According to the textbook, an example of a tax cost KPI would be: a. levels of late filing or error penalties. b. ETR (effective tax rate). c. employee turnover of the tax personnel. d. levels of technology/tax training.

b. ETR (effective tax rate).

What describes finding correspondences between at least two types of text or entries that may not match perfectly? a. Incomplete linkages b. Fuzzy matching c. Incomplete matching d. Algorithmic matching

b. Fuzzy matching

Which of the following describes part of the goal of the ETL process? a. Load the data into a relational database for storage. b. Identify and obtain the data needed for solving the problem. c. Identify which approach to data analytics should be used. b. Communicate the results and insights found through the analysis.

b. Identify and obtain the data needed for solving the problem.

Why is Supplier ID considered to be a primary key for a Supplier table? a. It is used to identify different supplier categories. b. It contains a unique identifier for each supplier. c. It is a 10-digit number. d. It can either be for a vendor or a miscellaneous provider.

b. It contains a unique identifier for each supplier.

_______ data would be considered the least sophisticated type of data. a. Ratio b. Nominal c. Ordinal d. Interval

b. Nominal

Which testing approach would be useful in assessing the value of inventory shrinkage given multiple environmental factors? a. Applied statistics b. Regression c. Sentiment analysis d. Probability

b. Regression

Which of the following is not a typical example of nominal data? a. Gender b. SAT scores c. Hair color d. Ethnic group

b. SAT scores

In the late 1960s, Ed Altman developed a model to predict if a company was at severe risk of going bankrupt. He called his statistic Altman's Z-score, now a widely used score in finance. Based on the name of the statistic, which statistical distribution would you guess this came from? a. Normal distribution b. Standardized normal distribution c. Poisson distribution d. Uniform distribution

b. Standardized normal distribution

According to the textbook, an example of a tax risk KPI would be: a. levels of technology/tax training. b. levels of late filing or error penalties. c. employee turnover of the tax personnel. d. ETR (effective tax rate).

b. levels of late filing or error penalties.

Exhibits 4-12 gives chart suggestions for what data you'd like to portray. Those options include all of the following except: a. outlier detection. b. normal distribution curves. c. relationship between variables. d. geographic data.

b. normal distribution curves.

According to the textbook, an example of a tax sustainability KPI would be: a. levels of technology/tax training. b. number of audits closed and significance of assessment over time. c. frequency of concerns pertaining to the organization's tax position. d. level of job satisfaction of the tax personnel.

b. number of audits closed and significance of assessment over time.

Benford's law suggests that the first digit of naturally occurring numerical datasets follow an expected distribution where: a. the leading digit of 4 is more common than 3. b. the leading digit of 8 is more common than 9. c. the leading digit of 9 is more common than 2. d. the leading digit of 6 is more common than 5.

b. the leading digit of 8 is more common than 9.

In general, the simpler the model, the greater the chance of: a. overfitting the data. b. underfitting the data. c. the need to reduce the amount of data considered. d. pruning the data.

b. underfitting the data.

As mentioned in the chapter, which of the following is not a common way that data will need to be cleaned after extraction and validation? a. Remove headings and subtotals. b. Correct inconsistencies across data. c. Clean up trailing zeroes. d. Format negative numbers.

c. Clean up trailing zeroes.

CAATs are automated scripts that can be used to validate data, test controls, and enable substantive testing of transaction details or account balances and generate supporting evidence for the audit. What does CAAT stand for? a. Computerized audit aids and tests b. Computer-aided audit techniques c. Computer-assisted audit techniques d. Computerized audit and accounting techniques

c. Computer-assisted audit techniques

Auditing financial statements, and its desire to look for errors, anomalies, and possible fraud, is most consistent with which type of analytics? a. Prescriptive analytics b. Predictive analytics c. Diagnostic analytics d. Descriptive analytics

c. Diagnostic analytics

Which approach to data analytics attempts to predict a relationship between two data items? a. Similarity matching b. Classification c. Link prediction d. Co-occurrence grouping

c. Link prediction

Which data approach attempts to predict connections between two data items? a. Regression b. Classification c. Link prediction d. Profiling

c. Link prediction

Line charts are not recommended for what type of data? a. Continuous data b. Trend lines c. Qualitative data d. Normalized data

c. Qualitative data

What is the most appropriate chart when showing a relationship between two variables (according to Exhibit 4-12)? a. Histogram b. Bar chart c. Scatter chart d. Pie graph

c. Scatter chart

The determinants for sample size include all of the following except: a. estimated misstatement. b. confidence level. c. potential risk of account. d. tolerable misstatement.

c. potential risk of account.

Tax departments interested in maintaining their own data are likely to have their own: a. tax reporting system. b. tax analytics. c. tax data mart. d. tax dashboard.

c. tax data mart.

Predictive analysis of potential tax liability and the formulation of a plan to reduce the amount of taxes paid is defined as: a. tax data analytics b. tax compliance data c. tax planning d. tax data warehouses

c. tax planning

Anscombe's Quartet suggests that: a. statistics should be used instead of visualizations b. visualizations should be used instead of statistics. c. visualizations should be used in tandem with statistics.

c. visualizations should be used in tandem with statistics.

The evaluation of the impact of different tax scenarios/alternatives on various outcome measures including the amount of taxable income or tax paid is called: a. tax compliance b. tax visualizations c. what-if scenario analysis d. data warehousing

c. what-if scenario analysis

By the year 2024, the volume of data created, captured, copied, and consumed worldwide will be 149 _____________ a. yottabytes b. exabytes c. zettabytes d. petabytes

c. zettabytes

An observation about the frequency of leading digits in many real-life sets of numerical data is called: a. clustering. b. leading digits hypothesis. c. Moore's law. d. Benford's law.

d. Benford's law.

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. Similarity matching b. Co-occurrence grouping c. Regression d. Classification

d. Classification

The metadata that describes each attribute in a database is which of the following? a. Flat file b. Descriptive attributes c. Composite primary key d. Data dictionary

d. Data dictionary

Which of these terms is defined as being a central repository of descriptions for all of the data attributes of the dataset? a. Data Analytics b. Big Data c. Data warehouse d. Data dictionary

d. Data dictionary

Which type of audit analytics might be used to find hidden patterns or variables linked to abnormal behavior? a. Descriptive analytics b. Prescriptive analytics c. Predictive analytics d. Diagnostic analytics

d. Diagnostic analytics

Which items would be currently out of the scope of Data Analytics? a. Evaluation of time stamps to evaluate workflow b. Duplicate payment of invoices c. Evaluation of phantom vendors d. Direct observation of processes

d. Direct observation of processes

Which of the following questions are NOT suggested by the Institute of Business Ethics to allow a business to create value from data use and analysis, and still protect the privacy of stakeholders? a. Does the company have the appropriate tools to mitigate the risks of data misuse? b. Does the company send a privacy notice to individuals when their personal data is collected? c. How does the company use data, and to what extent is it integrated into firm strategy? d. Does the data used by the company include personally identifiable information?

d. Does the data used by the company include personally identifiable information?

_____________blank data would be considered the most sophisticated type of data. a. Ordinal b. Interval c. Nominal d. Ratio

d. Ratio

What type of analysis would help auditors find missing checks? a. Benford's law analysis b. Fuzzy matching c. Decision support systems d. Sequence check

d. Sequence check

Which data approach attempts to identify similar individuals based on data known about them? a. Regression b. Classification c. Data reduction d. Similarity matching

d. Similarity matching

In which stage of the IMPACT model (introduced in Chapter 1) would the use of tax cockpits fit? a. Perform test plan b. Master the data c. Address and refine results d. Track outcomes

d. Track outcomes

Letter grades of A, B, and C would be best described as an example of: a. ratio data. b. nominal data. c. interval data. d. ordinal data.

d. ordinal data.

These data are organized and reside in a fixed field with a record or a file. Such data are generally contained in a relational database or spreadsheet and are readily searchable by search algorithms. The term matching this definition is: a. unstructured data. b. training data. c. test data. d. structured data.

d. structured data.

Models associated with regression and classification data approaches have all have these important parts except: a. identifying which variables (we'll call these independent variables) might help predict an outcome (we'll call this the dependent variable). b. the numeric parameters of the model (detailing the relative weights of each of the variables associated with the prediction). c. the functional form of the relationship (linear, nonlinear, etc.). d. test data.

d. test data.

The purpose of transforming data is: a. to load the data into the appropriate tool for analysis. b. to identify which data are necessary to complete the analysis. c. to obtain the data from the appropriate source. d. to validate the data for completeness and integrity.

d. to validate the data for completeness and integrity.


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