Data-Driven Decision Making
Exam Answer Key
Course Introduction
Data-Driven Decision Making explores the principles and practices of using data analytics to inform and support effective business and organizational decisions. Through a combination of theoretical concepts and hands-on applications, this course introduces students to data collection, data cleaning, exploratory analysis, and visualization techniques. Students will learn how to transform raw data into actionable insights, develop critical thinking and problem-solving skills, and apply various statistical and machine learning models to real-world scenarios. The course also examines ethical considerations and best practices for communicating data-driven findings to diverse audiences, preparing students to become informed decision-makers in any professional context.
Recommended Textbook
Essentials of Business Analytics 1st Edition by Jeffrey D. Camm
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688 Verified Questions
688 Flashcards
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Page 2
Chapter 1: Introduction
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Sample Questions
Q1) Web sites and social media sites use descriptive and advanced analytics to data collected in online experiments:
A) to position ads for the promotion of products and services.
B) to schedule staff and vehicle.
C) to design its premium seating offerings.
D) to decide how much to offer players in contract negotiations.
Answer: A
Q2) The disadvantage of online experimentation is:
A) it fails to promote sales.
B) it uses trial-and-error to statistically determine the difference in the Web site traffic and sales.
C) its experiments are conducted with risk in disruption of the overall business.
D) it fails to track the results of different versions of a Web site.
Answer: B
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Chapter 2: Descriptive Statistics
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Sample Questions
Q1) Compute IQR for the following data.
10 15 17 21 25 12 16 11 13 22
A) 6.25
B) 7.75
C) 5.14
D) 9.50
Answer: D
Q2) The correlation coefficient will always take values
A) greater than 0.
B) between -1 and 0.
C) between -1 and +1.
D) less than -1.
Answer: C
Q3) _____ are collected from several entities at the same point in time.
A) Time series data
B) Categorical and quantitative data
C) Cross-sectional data
D) Random data
Answer: C
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Page 4
Chapter 3: Data Visualization
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61 Flashcards
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Sample Questions
Q1) A line chart displaying the data values collected over a period of time is termed as a A) boxplot.
B) frequency graph.
C) dot plot
D) time series plot.
Answer: D
Q2) Using multiple lines on a line chart or employing multiple charts is an alternative to a A) column chart.
B) line chart.
C) two-dimensional graph.
D) three-dimensional chart.
Answer: D
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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Chapter 4: Linear Regression
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Sample Questions
Q1) In the simple linear regression model, the _____ accounts for the variability in the dependent variable that cannot be explained by the linear relationship between the variables.
A) constant term
B) error term
C) model parameter
D) residual
Q2) _____ is the data set used to build the candidate models.
A) Range
B) Codomain
C) Validation set
D) Training set
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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6
Chapter 5: Time Series Analysis and Forecasting
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Sample Questions
Q1) A forecast is defined as a(n):
A) prediction of future values of a time series.
B) quantitative method used when historical data on the variable of interest are either unavailable or not applicable.
C) set of observations on a variable measured at successive points in time.
D) outcome of a random experiment.
Q2) The process of _____ might be used to determine the value of smoothing constant that minimizes the mean squared error.
A) quantization
B) nonlinear optimization
C) clustering
D) curve fitting
Q3) The value of an independent variable from the prior period is referred to as a _____.
A) lagged variable
B) dummy variable
C) predictor variable
D) categorical variable
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Chapter 6: Data Mining
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Sample Questions
Q1) The simplest measure of similarity between observations consisting solely of categorical variables is given by _____.
A) the Euclidean distance
B) the Ward's distance
C) matching coefficient
D) Jaccard's coefficient
Q2) The process of reducing the number of variables to consider in a data-mining approach without losing any crucial information is termed as _____.
A) dimension reduction
B) data sampling
C) data reduction
D) aggregation
Q3) Observation refers to the:
A) estimated continuous outcome variable.
B) set of recorded values of variables associated with a single entity.
C) goal of predicting a categorical outcome based on a set of variables.
D) mean of all variable values associated with one particular entity.
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8
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(n) _____ refers to a model input that the decision maker can control in a what-if model.
A) decision variable
B) outlier
C) parameter
D) dummy variable
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Page 9
Chapter 8: Linear Optimization Models
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Sample Questions
Q1) A scenario in which the optimal objective function contour line coincides with one of the binding constraint lines on the boundary of the feasible region leads to _____ solutions.
A) infeasible
B) alternative optimal
C) binding
D) unique optimal
Q2) The shadow price of nonbinding constraints
A) will always be zero.
B) always take positive values.
C) can never be equal to zero.
D) is no longer valid if the right-hand side of the constraint remains the same.
Q3) Reference - 8.2: Which of the following visualization tools could help understand this problem better?
A) A time-series plot
B) A scatter chart
C) A network graph
D) A contour plot
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10
Chapter 9: Integer Linear Optimization Models
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Sample Questions
Q1) Reference - 9.1. The part-worths for each of the attribute levels obtained from an initial customer survey and the subsequent regression analysis can be used to determine the:
A) customer utility value.
B) optimal solution for the regression analysis.
C) overall profit for the company.
D) overall sales achieved by the company.
Q2) The importance of _____ for integer linear programming problems is often intensified by the fact that a small change in one of the coefficients in the constraints can cause a relatively large change in the value of the optimal solution.
A) objective function
B) decision variables
C) sensitivity analysis
D) optimization analysis
Q3) In binary integer linear program, the integer variables take only the values:
A) 0 or 1.
B) 0 or .
C) 1 or .
D) 1 or -1.
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Page 11
Chapter 10: Nonlinear Optimization Models
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Sample Questions
Q1) Consider the objective function, \( Y=A \times L^{\alpha} \times K^{\beta} \) where,
Y = total output
A= total-factor productivity
L = labor input
K= capital input = capital input share of contribution for L = capital input share of contribution for K
a. Assume = 0.33, = 0.67, A = 10 and each unit of labor costs $45 and each unit of capital costs $55. With $50,000 available in the budget, develop an optimization model to determine the number of units of capital and labor required in order to maximize output.
b. Find the optimal solution to the model you formulated in part a. Round all your answers to two decimal places. (Hint: When using Excel Solver, use the Multistart option with bounds 0 L 700 and 0 K 1000.)
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12
Chapter 11: Monte Carlo Simulation
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Sample Questions
Q1) For a given mean and standard deviation, the _____ function in Excel is used to generate a value for the random variable characterized by a normal distribution.
A) NORM.INV
B) RAND
C) VLOOKUP
D) FREQUENCY
Q2) Which of the following parameters is required to convert a computer-generated random variable into a uniform random variable?
A) Range of the distribution
B) Mean of the distribution
C) Variance of the distribution
D) Moments of the distribution
Q3) Which of the following is true of verification?
A) It is largely a debugging task.
B) It requires an agreement among analysts and managers.
C) It deals with the accurate modeling of real system operations.
D) It is performed prior to the development of the computer procedure for simulation.
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13
Chapter 12: Decision Analysis
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Sample Questions
Q1) Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: -$3000, -$1500, $0, $1500, $3000, $4500, $6000, $7500, $9000.
Q2) A measure of the outcome of a decision such as profit, cost, or time is known as a _____.
A) branch
B) payoff
C) regret
D) forecasting index
Q3) A(n) _____ refers to the result obtained when a decision alternative is chosen and a chance event occurs.
A) payoff table
B) outcome
C) state of nature
D) node
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