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Solution Manual for Introduction to Business Analytics, 1st Edition By Vernon Richardson and Marcia Watson Verified Chapter's 1 - 12 | Complete 

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TABLE OF CONTENTS Chapter 1: Specify the Question: Using Business Analytics to Address Business Questions Chapter 2: Obtain the Data: An Introduction to Business Data Sources Chapter 3: Analyze the Data: Basic Statistics and Tools Required in Business Analytics Chapter 4: Analyze the Data: Exploratory Business Analytics (Descriptive Analytics and Diagnostic Analytics) Chapter 5: Analyze the Data: Confirmatory Business Analytics (Predictive Analytics and Prescriptive Analytics) Chapter 6: Report the Results: Using Data Visualization Chapter 7: Marketing Analytics Chapter 8: Accounting Analytics Chapter 9: Financial Analytics Chapter 10: Operations Analytics Chapter 11: Advanced Business Analytics Chapter 12: Using the SOAR Analytics Model to Put It All Together: Three Capstone Projects   Chapter 1 End-of-Chapter Assignment Solutions Multiple Choice Questions 1. (LO 1.1) A coordinated, standardized set of activities conducted by both people and equipment to accomplish a specific business task is called . a. business processes b. business analysis c. business procedure d. business value 2. (LO 1.2) According to the information value chain, data combined with context is a. Information. b. Knowledge. c. Insight. d. Value. 3. (LO 1.5) Which phase of the SOAR analytics model addresses the proper way to communicate results to the decision maker? a. Specify the question b. Obtain the data c. Analyze the data d. Report the results 4. (LO 1.5) Which phase of the SOAR analytics model involves finding the most appropriate data needed to address the business question? a. Specify the question b. Obtain the data c. Analyze the data d. Report the results 5. (LO 1.5) Which questions seek information about Tesla’s sales in the next quarter? a. What happened? What is happening? b. Why did it happen? What are the causes of past results? c. Will it happen in the future? What is the probability something will happen? Can we forecast what will happen? d. What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints? 6. (LO 1.5) Which questions seek information on the routing of products from Queretaro, Mexico to Chicago, United States in the last quarter? a. What happened? What is happening? b. Why did it happen? What are the causes of past results? c. Will it happen in the future? What is the probability something will happen? Can we forecast what will happen? d. What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints? 7. (LO 1.5) Which questions ask why net income is increasing when revenues are decreasing, counter to expectations? a. What happened? What is happening? b. Why did it happen? What are the causes of past results? c. Will it happen in the future? What is the probability something will happen? Can we forecast what will happen? d. What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints? 8. (LO 1.5) Which questions help managers understand how to organize future shipments based on expected demand? a. What happened? What is happening? b. Why did it happen? What are the causes of past results? c. Will it happen in the future? What is the probability something will happen? Can we forecast what will happen? d. What should we do, based on what we expect will happen? How do we optimize our performance based on potential constraints? 9. (LO 1.5) Which term refers to the combined accuracy, validity, and consistency of data stored and used over time? a. Data integrity b. Data overload c. Data value d. Information value 10. (LO 1.3) A specialist who knows how to work with, manipulate, and statistically test data is a a. decision maker. b. data scientist. c. data analyst. d. decision scientist. 11. (LO 1.4) Which type of analysts predicts the amount of money that a company will receive from its customers to help management evaluate future investments based on expected investment performance, such as investments in equipment or employee training? a. Marketing analyst b. Operations analyst c. Financial analyst d. Accounting analyst 12. (LO 1.4) Which type of analyst addresses questions regarding tax and auditing? a. Marketing analyst b. Operations analyst c. Financial analyst d. Accounting analyst 13. (LO 1.5) Suppose a company has timely product reviews that are available when needed, but the reviews are biased. These product reviews are which type of data? a. Reliable b. Relevant c. Curated d. Consistent © McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC. 14. (LO 1.6) Which common visualization type shows trends in values over time? a. Line graph b. Scatterplot c. Pie chart d. Bar chart 15. (LO 1.6) Which common visualization type shows the composition of values over time? a. Line graph b. Scatterplot c. Pie chart d. Bar chart Discussion Questions 1. (LO 1.1) Give five examples of business processes at Tesla. How do they create business value for Tesla and its shareholders? Suggested Solution: Answers will vary, 1. Tesla procures automobile parts from auto suppliers – Because of Tesla’s unique styling, getting quality parts from its suppliers on a timely basis will support its manufacturing business. 2. Tesla manufactures batteries for its electric vehicle at its desired specifications – The quantity and quality of its batteries are of critical importance to Tesla. 3. Accepting and processing preorders from its customers – Tesla receives some indication of the demand for each of its products, that helps with planning. 4. Tesla markets its products – Tesla works to get Tesla products in the front of mind for its customers. 5. Tesla car and truck design – Tesla designs its automobiles in a way that will appeal to its customers (for example, Cybertruck). 2. (LO 1.2) Explain the information value chain by summarizing how data are transformed into knowledge insights for decision-making. Use the example of a book review on Amazon and how it might lead Amazon to decide how many of those books to stock at its warehouses. Suggested Solution: Amazon allows those who purchase books and other products at its website to give product reviews and assign product ratings. The product reviews may provide text which textual analytics could use to understand the general sentiment about the specific book. The product rating could also be used to understand how well the book is liked by verified buyers. Statistical correlations could be run among product review sentiment, product ratings and product sales to help forecast demand for the product. This will help Amazon determine how many books to keep in its warehouse ready for delivery. This is an example of how data turns into information, knowledge and ultimately helps with decision making. 3. (LO 1.3) Explain the information value chain by summarizing how data are transformed into knowledge insights for decision-making. Use the example of a book review of this book on Amazon and how it might help the publisher, McGraw Hill, determine whether to revise this book for a new, updated edition as the discipline of data analytics evolves. McGraw Hill will use many determinants to determine how well each one of its textbooks are performing. They’ll look at overall sales of the book, compared to competitors. But they may also survey users to determine how well the book is liked, what is deficient in the book, what new topics should be considered, etc. All told, all of the data will be put together, analyzed, knowledge will be gained, and a decision will be made. 4. (LO 1.3) Explain the difference between a decision-maker, a data scientist, and a business analyst. What is the role of each? Suggested Solution: While there are not always definitive distinctions between these three positions, the decision maker needs questions answered before they can make data-informed decisions. The data scientist is most familiar with the data, as that is their specialty, collecting and maintaining data in databases, manipulating, transforming and analyzing data. The business analyst generally understands the business and the information needs of the decision maker, but also understands the data. The business analyst can serve as a go between, between the decision maker and the data scientist, all working together to make data-informed decisions. 5. (LO1.4) Compare and contrast marketing analytics with accounting analytics. How are they similar? How are they different? Suggested Solution: Both marketing and accounting analytics address management questions using appropriate data and analytics. But they also differ from each other. For example, marketing analytics are used to address the needs of the marketing department, the business of promoting and selling products and services. Marketing analytics is often involved in providing insights into customer preferences and trends. In contrast, accounting analytics uses business analytics to help measure accounting performance and address accounting questions, such as analyzing whether a company committed fraud or predicting future sales or earnings of a company.

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