1. The decision-making themes covered in Business Analytics: Data Analysis & Decision Making include which of the following?
a.
optimization techniques
b.
decision analysis with uncertainty
c.
structured sensitivity analysis
d.
all of these choices
ANSWER:
d
POINTS:
1
DIFFICULTY:
Easy | Bloom's: Knowledge
TOPICS:
A-Head: 1-2 Overview of the Book
OTHER:
BUSPROG: Analytic | DISC: Decision Making
2. Which statement is not true?
Dealing with uncertainty includes measuring uncertainty.
Dealing with uncertainty includes modeling uncertainty explicitly into the analysis.
Dealing with uncertainty includes eliminating uncertainty by using the normal probability distribution.
Dealing with uncertainty requires a basic understanding of probability.
c
A-Head: 1.2 Overview of the Book
3. What is not one of the important themes of your Business Analytics: Data Analysis & Decision Making text?
data analysis
dealing with uncertainty
decision making
data mining
4. Data analysis includes:
data description
data inference
the search for relationships in data
5. Which of the following is not one of the steps in the modeling process?
Select the scale for the model.
Collect and summarize data.
Verify the model.
Present the results.
e.
Implement the model and update it through time.
a
Easy | Bloom's: Comprehension
6. Which of the following would not be included under data analysis?
measuring uncertainty
search for relationships
7. The decision making process includes:
optimization techniques for problems with no uncertainty
decision analysis for problems with uncertainty
sensitivity analysis
8. Which tool is an Excel® add-in for performing what-if analyses?
PrecisionTree
TopRank
Solver
@Risk
StatTools
b
9. Which of the following statements are true?
Three important themes run through the book: data analysis, decision making, and uncertainty.
Data analysis includes data description, data inference, and the searching for relationships in data
Decision making includes optimization techniques for problems with no uncertainty, decision analysis for problems with uncertainty, and structured sensitivity analysis.
Dealing with uncertainty includes measuring uncertainty and modeling uncertainty explicitly into the analysis.
All of these statements are true.
e
10. Data analysis includes data description, data inference, and the search for relationships in data.
True
False
11. Decision-making includes optimization techniques for problems with certainty, decision analysis for problems with certainty, and structured sensitivity analysis.
12.
A relatively new aspect of business analytics is big data, which typically implies the analysis of the very large data sets that companies currently encounter.
13. Three important themes run through the Business Analytics: Data Analysis & Decision Making text: data analysis, decision-making, and dealing with uncertainty.
14. Spreadsheet simulations cannot be performed entirely with the built-in or add-in tools in Excel®, so spreadsheet simulations are still one of the most difficult quantitative models to implement in the business world.
BUSPROG: Analytic | DISC: Data Methods
15. Although it is relatively easy to collect data, it can be more challenging to understand what the data mean.
16. When we use simulation models to help make decisions, we do not deal with uncertainty at all, since we often must make inferences from the simulated data.
17. We must deal with uncertainty when we make inferences from data and search for relationships in data, or when we use decision trees to help make decisions.
18. @Risk is an Excel® add-in that can be used to run replications of a simulation, keep track of outputs, create useful charts, and perform sensitivity analyses.
19. Which of the following statements is false?
The modeling process discussed in your text is a five-step process.
Uncertainty is a key aspect of most business problems.
Data description and data inference are data analysis themes.
Easy | Bloom's Knowledge
A-Head: 1.2 Overview of the Book | 1.3 Models and Modeling
20. Which of the following statements are false?
Decision-making includes optimization techniques for problems with certainty, decision analysis for problems with certainty, and structured sensitivity analysis.
Graphical models can be very helpful for simple problems. For complex problems, however, graphical models usually fail to show the important elements of a problem and how they are related.
All of these statements are false.
21. Which of the following statements are true?
A fairly recent alternative to algebraic modeling is spreadsheet modeling. Instead of relating various quantities with algebraic equations and inequalities, we relate them in a spreadsheet with cell formulas.
Data are usually meaningless until they are analyzed for trends, patterns, relationships, and other useful information
Algebraic models, by means of algebraic equations and inequalities, specify a set of relationships in a very precise way. Their main drawback is that they require an ability to work with abstract mathematical symbols.
When we make inferences from data and search for relationships in data, or when we use decision trees to help make decisions, we must deal with uncertainty.
22. What is not one of the types of models described in your Business Analytics: Data Analysis & Decision Making text?
algebraic model
spreadsheet model
scale model
graphical model
A-Head: 1.3 Modeling and Models
23. The modeling process discussed in your Business Analytics: Data Analysis & Decision Making text is a:
seven-step process
six-step process
five-step process
four-step process
three-step process
A-Head: 1.3 Models and Modeling
24. Which is an Excel® add-in for simulation?
25. The authors of the Business Analytics: Data Analysis & Decision Making text describe three types of models: graphical models, algebraic models, and spreadsheet models.
26. Graphical models are the least intuitive type of model.
27. The overall modeling process typically done in the business world always require seven steps: define the problem, collect and summarize data, formulate a model, verify the model, select one or more suitable decisions, present the results to the organization, and finally implement the model and update it through time.
28. Algebraic models, by means of algebraic equations and inequalities, specify a set of relationships in a very precise way, but they require an ability to work with abstract mathematical symbols.
29. A fairly recent alternative to algebraic modeling is spreadsheet modeling, which, instead of relating various quantities with algebraic equations and inequalities, relates them in a spreadsheet with cell formulas.
30. Graphical models are the most quantitative type of model.
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