Ch1 Test Bank The Roles Of Data And Predictive Analytics In - Predictive Analytics 1e Complete Test Bank by Jeff Prince. DOCX document preview.
Predictive Analytics for Business Strategy, 1e (Prince)
Chapter 1 The Roles of Data and Predictive Analytics in Business
1) Which of the following business strategies has a strong business analytics focus?
A) Using data on historical sales to build a recommendation service for your product portfolio.
B) Building a market presence through franchising.
C) Building a reputation for high quality through informative advertising.
D) Ensuring high quality through vertically integrating.
2) An appealing alternative to using "rules of thumb" and "gut feelings" in formulating business strategies includes:
A) not deviating from the firm's previously established practices.
B) being an early adopter of business strategies of industry leaders.
C) business strategies justified from evidence-based business analytics.
D) None of these choices are correct.
3) A plan of action designed by a business practitioner to achieve a business objective would be best described as:
A) business analytics.
B) predictive analytics.
C) business strategy.
D) a database.
4) A necessary foundational element for a business to organize the collection of data that the firm will use to analyze is:
A) the HR department.
B) cloud-based storage.
C) the IT department.
D) a database.
5) Which of the following statements best summarizes the use of business analytics?
A) The use of data analysis to aid in business decision making.
B) Using of cluster analysis to create customer categories.
C) Forecasting stock prices.
D) Using "big data" methods to predict sales.
6) Suppose you collect a series of pictures from Facebook and wish to perform analysis on them. The collection of pictures you've gathered is an example of what type of data?
A) Unstructured data
B) Incomplete data
C) Structured data
D) Censored data
7) Suppose you collect a series of texts from CEOs' public speaking engagements and wish to perform analysis on them. The collection of texts you've gathered is an example of what type of data?
A) Unstructured data
B) Incomplete data
C) Structured data
D) Censored data
8) Suppose you collect monthly sales figures for each store location in your company as well as the wages paid to employees for each store, and that you have a complete history for the last ten years for each store. Provided this information is in table format, the information you've gathered is an example of what type of data?
A) Unstructured data
B) Incomplete data
C) Structured data
D) Censored data
9) Suppose you collect a series of texts from statements made of a sample of potential customers as they watch an advertisement for your company's product. The collection of texts you've gathered from these statements is an example of what type of data?
A) Structured data
B) Incomplete data
C) Unstructured data
D) Panel data
10) Use the following dataset to answer the following question.
Name | Month | Commission | Tenure | Travel Expense |
Sophie Castro | 1 | $48,000 | 4 years | $11,000 |
Travis Turner | 1 | $53,000 | 7 years | $21,000 |
Elias Hansen | 2 | $67,000 | 10 years | $7,000 |
Amanda Garza | 2 | $72,000 | 8 years | $14,000 |
What is the unit of observation?
A) Month-tenure
B) Person-month
C) Month
D) Tenure
11) Use the following dataset to answer the following question.
Name | Month | Commission | Tenure | Travel Expense |
Sophie Castro | 1 | $48,000 | 4 years | $11,000 |
Travis Turner | 1 | $53,000 | 7 years | $21,000 |
Elias Hansen | 2 | $67,000 | 10 years | $7,000 |
Amanda Garza | 2 | $72,000 | 8 years | $14,000 |
What type of dataset is this?
A) Cross-sectional
B) Time series
C) Pooled cross-section
D) Panel
12) Use the following dataset to answer the following question.
Firm | Year | # of Employees | Sales | Profits |
Jim's Auto | 2014 | 23 | $741,000 | $52,000 |
Mechanic Zone | 2014 | 15 | $510,000 | -$72,000 |
Jim's Auto | 2015 | 31 | $1,081,050 | $101,000 |
Mechanic Zone | 2015 | 27 | $811,000 | $28,000 |
What is the unit of observation?
A) Firm
B) Year
C) Year-Profits
D) Firm-Year
13) Use the following dataset to answer the following question.
Firm | Year | # of Employees | Sales | Profits |
Jim's Auto | 2014 | 23 | $741,000 | $52,000 |
Mechanic Zone | 2014 | 15 | $510,000 | -$72,000 |
Jim's Auto | 2015 | 31 | $1,081,050 | $101,000 |
Mechanic Zone | 2015 | 27 | $811,000 | $28,000 |
What type of dataset is this?
A) Cross-sectional
B) Time-series
C) Pooled cross-section
D) Panel
14) Use the following dataset to answer the following question.
State | Year | Sales Tax | Sales per Store | Employees per Store |
Indiana | 2014 | 7.25 | $650,000 | 50 |
Illinois | 2014 | 7.75 | $625,000 | 65 |
Indiana | 2015 | 8.00 | $800,050 | 75 |
Illinois | 2015 | 8.75 | $525,000 | 55 |
What is the unit of observation?
A) Panel
B) State
C) Sales-employee per store
D) State-year
15) Use the following dataset to answer the following question.
State | Year | Sales Tax | Sales per Store | Employees per Store |
Indiana | 2014 | 7.25 | $650,000 | 50 |
Illinois | 2014 | 7.75 | $625,000 | 65 |
Indiana | 2015 | 8.00 | $800,050 | 75 |
Illinois | 2015 | 8.75 | $525,000 | 55 |
What type of dataset is this?
A) Pooled cross-section
B) Panel
C) Time Series
D) State-year
16) Use the following dataset to answer the following question.
State | Year | Salary | Location | Sales Workshop? |
Aiden Rosen | 2017 | $98,000 | Seattle | Y |
Sadie Hubbard | 2017 | $83,000 | Chicago | N |
Jen Jordan | 2018 | $77,000 | Seattle | N |
Rob Jackson | 2018 | $79,000 | Chicago | N |
What is the unit of observation?
A) Person-salary
B) Person-year
C) Person-year-location
D) Salary
17) Use the following dataset to answer the following question.
State | Year | Salary | Location | Sales Workshop? |
Aiden Rosen | 2017 | $98,000 | Seattle | Y |
Sadie Hubbard | 2017 | $83,000 | Chicago | N |
Jen Jordan | 2018 | $77,000 | Seattle | N |
Rob Jackson | 2018 | $79,000 | Chicago | N |
What type of dataset is this?
A) Panel
B) Time series
C) Pooled cross-section
D) Cross-section
18) Use the following dataset to answer the following question.
Stock | Day | Stock Price |
Apple | 5-13-18 | $189 |
Apple | 5-14-18 | $187 |
Apple | 5-15-18 | $185 |
Apple | 5-16-18 | $188 |
What is the unit of observation?
A) Apple-stock price
B) Day-price
C) Day
D) Stock price
19) Use the following dataset to answer the following question.
Stock | Day | Stock Price |
Apple | 5-13-18 | $189 |
Apple | 5-14-18 | $187 |
Apple | 5-15-18 | $185 |
Apple | 5-16-18 | $188 |
What type of dataset is this?
A) Panel
B) Unstructured
C) Pooled cross-section
D) Time series
20) Use the following dataset to answer the following question.
Name | Year | Salary | Tenure | MBA? |
Dmitry Haas | 2017 | $98,000 | 5 years | Y |
Jackie Bay | 2017 | $83,000 | 3 years | N |
Renee Topkis | 2017 | $77,000 | 12 years | Y |
Maria Val | 2017 | $79,000 | 8 years | N |
What is the unit of observation?
A) Person-salary
B) Person
C) Person-Tenure
D) Salary
21) Use the following dataset to answer the following question.
Name | Year | Salary | Tenure | MBA? |
Dmitry Haas | 2017 | $98,000 | 5 years | Y |
Jackie Bay | 2017 | $83,000 | 3 years | N |
Renee Topkis | 2017 | $77,000 | 12 years | Y |
Maria Val | 2017 | $79,000 | 8 years | N |
What is the type of data set?
A) Pooled cross-section
B) Panel
C) Unstructured
D) Cross-section
22) Suppose you collect monthly sales figures for each store location in your company as well as the wages paid to employees for each store, and that you have a complete history for the last ten years for each store. What is the type of this data set?
A) Pooled cross-section
B) Unstructured data
C) Censored data
D) Panel
23) If commercial real estate costs of Kroger affect demand for Kroger Milk through the product prices Kroger charges to its customers, this is an example of what type of relationship?
A) A direct causal effect of real estate costs on product demand
B) An indirect causal effect of product prices on product demand
C) An indirect causal effect of product demand on product prices
D) An indirect causal effect of real estate costs on product demand
24) If advertising exposure, disposable income and price affect demand for a product, and advertising exposure affects the price of the product, what type of relationship is not present?
A) A direct causal effect of advertising exposure on product demand
B) A direct causal effect of advertising exposure on product prices
C) An indirect causal effect of disposable income on product demand
D) A direct causal effect of product prices on product demand
25) In describing the data-generating process for "click-throughs" for one of your firm's advertising campaigns you've assumed the following relationship: Yi = f (Hi, Ji) + Ui, where Yi is if individual i clicked through, Hi is individual i's household income, Ji is an indicator for whether or not individual i has a job. What type of factors might be contained in Ui?
A) A factor that affects Ji but does not affect Yi.
B) A factor that affects Hi but does not affect Yi.
C) A factor that affects Hi and Yi.
D) None of the answers is correct.
26) Suppose you've assumed the following two data-generating processes: (1) Yi = f (Hi, Ji) and (2) Ji = g (Xi, Zi). What do these assumptions imply?
A) J has a direct causal effect on H.
B) Z has a direct causal effect on Y.
C) X has an indirect causal effect on J.
D) Z has an indirect causal effect on Y.
27) Providing a graphical presentation of past trends of a set of critical indicators for a company is an example of what data presentation format?
A) Query
B) Report
C) KPIs (key performance indicators)
D) Dashboard
28) Presenting an assessment of variables of interest against a given benchmark for a company is an example of what data presentation format?
A) Query
B) Scorecard
C) KPIs (key performance indicators)
D) Dashboard
29) Identifying distinctive relationships between observations in a dataset is an example of what sort of data analysis?
A) Query
B) Pattern discovery
C) Mean
D) Covariance
30) In examining the career earnings of different undergraduate majors, identifying Michael Jordan as an atypical instance amongst Geography majors would be an example of what sort of data analysis?
A) Dashboard
B) Pattern discovery
C) Outlier detection
D) Data mining
31) The process of identifying distinctive relationships between observations in a data set, or pattern discovery, within a very large dataset is typically known as?
A) Data mining
B) Outlier detection
C) Query
D) Pattern discovery
32) In grouping customers into separate types according to their spending, internet browsing, payment method, and age a firm is engaging in what sort of analysis?
A) Data mining
B) Cluster analysis
C) Outlier detection
D) Linear regression
33) In examining the career earnings of individuals with different levels of college/graduate attainment, identifying Bill Gates as an atypical instance amongst the population with less than a bachelor's degree, would be an example of what sort of data analysis?
A) Query
B) Pattern discovery
C) Data mining
D) Outlier detection
34) Which of the following would not be an example of summary statistic of a variable within dataset?
A) Mean
B) Variance
C) Interquartile range
D) None of the above.
35) Any request for information from a database is an example of:
A) pattern discovery.
B) data mining.
C) query.
D) association analysis.
36) Quantitative measures meant to summarize and interpret properties of a dataset are instances of:
A) pivot tables.
B) descriptive statistics.
C) linear regressions.
D) outliers.
37) Use the following dataset to answer the following question.
State | Year | Sales | Capital Expenditures | Wages |
Western | 2016 | $750,000 | $130,000 | $330,000 |
Eastern | 2016 | $645,000 | $225,000 | $430,000 |
Western | 2017 | $770,050 | $145,000 | $230,000 |
Eastern | 2017 | $925,000 | $125,000 | $530,000 |
Using a spreadsheet software, such as Excel, to preview different views of this dataset, such as Sales in the Eastern part of the country, would be aided by what?
A) Linear regression
B) Cluster analysis
C) Pivot table
D) Scorecard
38) Use the following presentation to answer the following question.
State | Year | Sales per Store | Target | Performance |
Western | 2016 | $750,000 | $700,000 | Good |
Eastern | 2016 | $645,000 | $680,000 | Nearing Acceptable |
Western | 2017 | $770,050 | $745,000 | Good |
Eastern | 2017 | $925,000 | $825,000 | Good |
This presentation is an example of what?
A) Cluster analysis
B) Association analysis
C) Pivot table
D) Scorecard
39) Measures of the central tendencies of variables such as the mean, median, and mode are examples of:
A) descriptive statistics.
B) data mining.
C) covariance.
D) causal relationships
40) In grouping TV markets into separate types according to regional spending, demographics, and business activity, and cost of advertising is engaging in what sort of analysis?
A) Passive prediction
B) Cluster analysis
C) Data mining
D) Linear regression
41) Measures of the spread of variables such as the variance and range are examples of:
A) descriptive statistics.
B) data mining.
C) covariance.
D) causal relationships.
42) An analyst is attempting to understand whether the frequency of faulty units coming out of production last month is different for Eastern location plants relative to all plants across the entire company. This analyst is engaging in what type of data analysis?
A) Linear regression
B) Outlier detection
C) Cluster analysis
D) Association analysis
43) Gauging customer discontent for an airline by looking for patterns between unfavorable mentions on Twitter (a potentially large dataset) and on-time traffic departures would likely be an example of what type of data analysis?
A) Linear regression
B) Data mining
C) Outlier detection
D) Scorecard
44) Which of the following is an example of lead information?
A) Measurement of sales in response to a recently implemented ad campaign
B) Measurement of price sensitivity of customers in a given city
C) Measurement of rate of customer complaints following an employee training program
D) None of the answers is correct.
45) Which of the following is an example of lead information?
A) Measurement of number of employees enrolled in new HR workshop
B) Measurement of employee complaints following an employee training program
C) Measurement of wage sensitivity of employee retention in a given department
D) Measurement of number of employees hired since opening of new store location
46) Determining the average propensity of customers to purchase a warranty plan, if the plan is under a promotional offer during the time of product purchase, would be an example of what type of information?
A) Passive prediction
B) Lag information
C) Indirect causal effect
D) Lead information
47) Which of the following is an example of lag information?
A) Measurement of faulty units in response to a recently implemented inventory method
B) Measurement of price sensitivity of customers in a given city
C) Measurement of rate of purchasing propensity following exposure to advertising
D) None of the answers is correct.
48) For a health care management company, indicators such as bed utilization, overtime wages, and patients served would represent what sort of information?
A) Unstructured
B) Indirect causal relationship
C) Key performance indicators
D) None of the answers is correct.
49) Suppose you want to answer the following question: "How will Sales of version 2.0 of our product change when we release version 3.0 of our product?" What type of data analysis is crucial toward answering this question?
A) Active prediction
B) Passive prediction
C) Data mining
D) OLAP cube
50) Suppose you want to answer the following question: "How will Sales of our product at our outdoor location change if it rains above average next week?" What type of data analysis is crucial toward answering this question?
A) Active prediction
B) Passive prediction
C) Dashboard
D) Pivot table
51) Using employment growth in the leisure and hospitality sector for the entire city of Indianapolis to predict yearly sales for your restaurant (in Indianapolis) is an example of:
A) passive prediction.
B) active prediction.
C) outlier detection.
D) scorecard.
52) Predicting how moving to a just-in-time production plan will affect employee productivity will require what sort of prediction?
A) Passive prediction
B) Active prediction
C) KPI
D) Lag information
53) The critical distinction between the effectiveness of engaging in active prediction versus passive prediction is that one or more of the variables of interest undergoes a(n):
A) lead information.
B) trend.
C) outlier detection.
D) exogenous change.
54) Common criteria to judge competing models to be used in passive prediction include:
A) degree of exogenous variation.
B) model fit.
C) data mining.
D) pattern discovery.
55) Which of the following business questions require active prediction?
A) How will employee retention change after introducing a new-hire workshop?
B) Are older or younger employees more likely to stay with the firm?
C) Which department within the company has the highest turnover rate?
D) Do high performance employees have higher tenures with the firm?