Business Decision Modeling Test
Bank
Course Introduction
Business Decision Modeling introduces students to the quantitative tools and methodologies used to support effective decision-making in organizations. The course covers concepts such as decision analysis, optimization, simulation, and risk assessment, utilizing techniques like linear programming, decision trees, and sensitivity analysis. Emphasizing practical application, students learn to structure complex business problems, analyze data, and interpret results using contemporary spreadsheet software and modeling platforms. Through case studies and real-world scenarios, the course prepares students to approach managerial decisions systematically and make informed choices that enhance business performance.
Recommended Textbook Essentials of Business Analytics 1st Edition by
Jeffrey D. Camm
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12 Chapters
688 Verified Questions
688 Flashcards
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Page 2
Chapter 1: Introduction
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Sample Questions
Q1) Supply network design models provide the cost-minimizing plant and distribution center locations subject to meeting the customer service requirements. This model is referred as
A) Optimization models.
B) Forecasting models.
C) Data mining models.
D) Network models.
Answer: A
Q2) When a decision maker is faced with several decision alternatives and an uncertain set of future events. He/She uses ______ to develop an optimal strategy.
A) utility theory
B) predictive analytics
C) data mining
D) decision analysis
Answer: D
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Page 3
Chapter 2: Descriptive Statistics
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Sample Questions
Q1) Consider a sample on the waiting times (in minutes), at the billing counter in a grocery store, to be 15, 24, 18, 15, 21, 20, 15, 22, 19, 16, 15, 22, 20, 15, and 21. Compute the mean, median, and mode.
Answer: Mean = 18.53.
Median = 19.
Mode = 15.
Q2) Data collected from several entities over several time periods is A) categorical and quantitative datA)
B) time series data.
C) source data.
D) cross-sectional data.
Answer: B
Q3) A set of values corresponding to a set of variables is defined as a(n) _____. A) quantity
B) event
C) factor
D) observation
Answer: D
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4
Chapter 3: Data Visualization
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Sample Questions
Q1) If the scatter chart indicates a positive linear relationship between two variables, then their correlation coefficient is
A) equal to -1.
B) greater than 1.
C) between 0 and +1.
D) between -1 and 0.
Answer: C
Q2) We create multiple dashboards
A) to help the user scroll vertically and horizontally to see the entire dashboard.
B) so that each dashboard can be viewed on a single screen.
C) to make sure the KPIs are not displayed in the data dashboard.
D) so that all dashboards can be viewed on a single screen.
Answer: B
Q3) A crosstabulation in Microsoft Excel is known as a
A) scatter plot.
B) bar chart.
C) histogram.
D) PivotTable.
Answer: D
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Page 5
Chapter 4: Linear Regression
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Sample Questions
Q1) The coefficient of determination:
A) takes values between -1 to +1.
B) is equal to zero for a perfect fit.
C) is equal to one for the poorest fit.
D) is used to evaluate the goodness of fit.
Q2) In the graph of the simple linear regression equation, the parameter o represents the _____ of the regression line.
A) slope
B) x-intercept
C) y-intercept
D) end-point
Q3) In the graph of the simple linear regression equation, the parameter 1 is the _____ of the regression line.
A) slope
B) x-intercept
C) y-intercept
D) end-point
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Chapter 5: Time Series Analysis and Forecasting
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Sample Questions
Q1) Which of the following states the objective of time series analysis?
A) To study the variation of time with respect to increase in the variable value
B) To analyze the time-dependent environmental factors that affected variable values in the past
C) To use present variable values to study what should have been the ideal past values
D) To uncover a pattern in the time series and then extrapolate the pattern into the future
Q2) Trend refers to:
A) the long-run shift or movement in the time series observable over several periods of time.
B) the outcome of a random experiment.
C) the recurring patterns observed over successive periods of time.
D) the short-run shift or movement in the time series observable at some specific period of time.
Q3) _____ uses a weighted average of past time series values as the forecast.
A) The qualitative method
B) Exponential smoothing
C) Correlation analysis
D) The causal model
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Page 7
Chapter 6: Data Mining
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Sample Questions
Q1) _____methods do not attempt to predict an output value but are rather used to detect patterns and relationships in the data.
A) Supervised learning
B) Machine learning
C) Artificial intelligence
D) Unsupervised learning
Q2) The endpoint of a k-means clustering algorithm occurs when:
A) Euclidean distance between clusters is minimum.
B) Euclidean distance between observations in a cluster is maximum.
C) no further changes are observed in cluster structure and number.
D) all of the observations are encompassed within a single large cluster with mean k.
Q3) _____ is a category of data-mining techniques in which an algorithm learns how to predict or classify an outcome variable of interest.
A) Supervised learning
B) Unsupervised learning
C) Dimension reduction
D) Data sampling
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Chapter 7: Spreadsheet Models
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Sample Questions
Q1) A company asked one of their analysis team to analyze and create models that help decide whether they should manufacture a particular product or outsource its production. The different components are given below:
Fixed Cost, FC = $25,000
Material Cost per Unit, MC = $2.15
Labor Cost per Unit, LC = $2.00
Outsourcing Cost per Unit, O = $4.50
Note that per-unit material and labor cost together make up the variable cost per unit. Use a two-way data table to show how the savings due to outsourcing changes as a function of different production volume and different bids on per-unit cost for outsourcing. Vary the production volume from 0 to 100,000 in increments of 10,000. The six bids are $3.11, $3.49, $4.50, $4.98, $5.12, and $5.45.
Q2) A one-way data table summarizes:
A) a single input's impact on the output of interest.
B) multiple input's impact on a single output of interest.
C) values of the input cells that will cause the single output value to equal zero.
D) values of cells when not all of the model is observable on the screen.
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Chapter 8: Linear Optimization Models
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Sample Questions
Q1) A(n) _____ solution satisfies all the constraint expressions simultaneously.
A) feasible
B) objective
C) infeasible
D) extreme
Q2) A(n) _____ refers to a set of points that yield a fixed value of the objective function.
A) objective function coefficient
B) infeasible solution
C) objective function contour
D) feasible region
Q3) Clever Sporting Equipment, Inc. makes two types of balls: Soccer balls and Cork balls. The making of each soccer ball and cork ball requires 3 hours and 4 hours of production time, respectively. For the next month, the total production hours of 500 are available. Also, it is given that the combined production quantity for these two balls must be at least 150 units. The objective for this linear programming model is to fulfil the given production requirements at a minimum cost for the total production. The production cost for each Soccer ball is $9 and each Cork ball is $7. Formulate and solve for the recommended production quantities.
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Chapter 9: Integer Linear Optimization Models
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Sample Questions
Q1) Which of the following is true of the relationship between the value of the optimal integer solution and the value of the optimal solution to the LP Relaxation?
A) For integer linear programs involving minimization, the value of the optimal solution to the LP Relaxation provides an upper bound on the value of the optimal integer solution.
B) For integer linear programs involving maximization, the value of the optimal solution to the LP Relaxation provides a lower bound on the value of the optimal integer solution.
C) For integer linear programs involving minimization, the value of the optimal solution to the LP Relaxation provides a lower bound on the value of the optimal integer solution.
D) For any linear program involving either minimization or maximization, the value of the optimal solution to the LP Relaxation provides an infeasible value for the optimal integer solution.
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Chapter 10: Nonlinear Optimization Models
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Sample Questions
Q1) Gatson manufacturing company is willing to promote 2 types of tires: Economy tire; Premium tire, and these two tires are independent of each other in terms of demand, cost, price, etc. An analytics team of this company has estimated the profit functions for both the tires as,
Monthly profit for Economy tire = 49.2415 LN(XA) + 180.414
Monthly profit for Premium tire = 84.344 LN(XB) - 150.112
where XA and XB are the advertising amount allocated to Economy tire and Premium tire, respectively, and LN is the natural logarithm function. The advertising budget is $200,000, and management has dictated that at least $20,000 must be allocated to each of the two tires.
(Hint: To compute a natural logarithm for the value X in Excel, use the formula =LN(X). For Solver to find an answer, you also need to start with decision variable values greater than 0 in this problem.)
Develop and solve an optimization model that will prescribe how the company should allocate its marketing budget to maximize profit.
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Page 12
Chapter 11: Monte Carlo Simulation
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Sample Questions
Q1) Reference - 11.1: Which of the following inferences can be drawn about the monthly salary?
A) The average monthly salary is $3000.
B) The monthly salary is always less than $3000.
C) The monthly salary is always greater than $3000.
D) The range of the monthly salary distribution is $3000 to $5000.
Q2) In a base-case scenario, the output is determined by assuming
A) worst values that can be expected for the random variables of a model.
B) the mean trial values for the random variables of a model.
C) best values that can be expected for the random variables of a model.
D) the most likely values for the random variables of a model.
Q3) Reference - 11.1: The type of distribution shown in the graph is A) uniform.
B) normal.
C) exponential.
D) beta.
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13
Chapter 12: Decision Analysis
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Sample Questions
Q1) The probabilities of both sample information and a particular state of nature occurring simultaneously are termed as _____.
A) joint probabilities
B) probable probabilities
C) preliminary probabilities
D) posterior probabilities
Q2) Chance nodes are
A) nodes provided at the end of the states-of-nature branches.
B) nodes indicating points where an uncertain event will occur.
C) nodes provided at the end of the decision alternative branches where a payoff is shown.
D) nodes indicating points where a decision is made.
Q3) The states of nature are defined so that they are _____. This means that at least one state of nature must occur at a given time for a chance event.
A) collectively exhaustive
B) mutually exclusive
C) certain events
D) optimistic outcomes
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