SOLUTIONS MANUAL for Introduction to Management Science 7th Edition A Modeling and Case Studies Approach with Spreadsheets by Hillier and Mark Hillier

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Analytics 7th Edition Hillier b b b b




CHAPTER 1 b



INTRODUCTIO
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Review Questions b



1.1 –1 The rapid development of the discipline began in the 1940’s and 1950’s.
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1.1 –2 The traditional name given to the discipline is operations research.
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1.1 –3 A management science study provides an analysis and recommendations, based on
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the quantitative factors involved in the problem, as input to the managers.
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1.1 –4 Management science is based strongly on some scientific fields, including mathematics and
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computer science. It also draws upon the social sciences, especially economics.
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1.1 –5 Many managerial problems revolve around such quantitative factors as production quantities,
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revenues, costs, the amounts available of needed resources, etc.
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1.2 –1 Business analytics has drawn on various other quantitative decision sciences, including
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management science, mathematics, statistics, computer science, information technology,
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industrial engineering, etc.
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1.2 –2 The era of big data is where massive amounts of data (accompanied by massive amounts
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of computational power) are now commonly available to many businesses to help guide
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managerial decision making. A primary focus of business analytics is on how to make the most
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effective use of all these data.
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1.2 –3 b Descriptive analytics uses innovative techniques (including algorithms) to explore the
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data, locate and extract the data that are relevant, and then identify the interesting
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patterns and summary data.
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1.2 –4 Predictive analytics often involves applying statistical models to predict future events or trends.
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1.2 –5 Prescriptive analytics uses powerful techniques drawn mainly from management science to
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prescribe what should be done in the future.
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1.2 –6 Data science tends to be more interdisciplinary, more based on scientific methods, more
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applicable to various areas in addition to business, and more concerned with how to deal with
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even massive amounts of data in various forms.
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1.2 –7 The goal of machine learning is to allow computers to learn automatically from historical
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relationships and trends in the data in order to do such things as making data-driven
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predictions.
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Machine learning is a popular method for applying predictive analytics by performing pattern
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recognition.
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1.2 –8 Machine learning is just one important part of artificial intelligence. Because its focus is
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on automatically learning from historical relationships and trends in the data, machine
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learning
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provides an ideal platform for performing artificial intelligence. The difficult part then is taking
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the next step to use this platform to truly simulate human thinking capability and behavior.
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Analytics 7th Edition Hillier
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1–1
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, ACCESS Test Bank for Introduction to Management Science and Business
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Analytics 7th Edition Hillier b b b b




1.3 –1 Business analytics provides a larger toolkit when dealing with descriptive analytics, data
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preparation, and predictive analytics. Management science techniques normally take the lead
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when performing prescriptive analytics.
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1.3 –2 Analytics have been making important contributions in such areas as sports, political
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campaigns, healthcare, combating crime, personal financial analysis, etc.
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1.3 –3 Top management now understands very well the impact that business analytics and
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management science can have on the bottom line. This will continue to require many more
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people who are very well trained in business analytics and management science
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1.3 –4 Operations research has been the usual name given to management science outside of
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business schools.
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1.3 –5 INFORMS (the Institute of Operations Research and the Management Sciences) is the largest
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professional society of management science and business analytics professionals or students in
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1.4 –1 Variable costs include all of the costs that are proportional with the number of units produced.
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1.4 –2 Fixed costs include the costs that are incurred regardless of how many units are produced.
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These might include a prorated share of the salaries for upper management, capital
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equipment,
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property taxes, and more. b b b




1.4 –3 There are often diminishing returns from advertising that are not captured by linear regression.
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1.4 –4 If a polynomial equation is used to try to predict what sales will be for advertising budgets, it
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bwill eventually start sloping downward. While we intuitively would expect diminishing returns
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bas advertising is increased, we wouldn’t expect sales to actually decrease.
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1.4 –5 Sales do not increase proportionally with the level of advertising, but rather
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increase proportionally with the square root of advertising.
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1.4–6 Solver will find the value of decision variable cells that will optimize the value of an
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objective cell.
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Problems
1.1 The three modules are the Incident Ticket Classification Module (which lists and classifies the
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undesirable incidents for the various servers), the Server Classification Module (which links
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the server unavailable incidents to the servers involved and then develops metrics for the
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individual servers), and the Remediation Recommendation Module (which develops
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recommendations of the appropriate modernization actions that should be taken for
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problematic servers).
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