Business Analytics Review Questions
Course Introduction
Business Analytics is an interdisciplinary course that introduces students to the concepts, techniques, and tools used to analyze data and support business decision-making. The course covers fundamental topics such as data collection and management, statistical analysis, predictive modeling, and data visualization. Students will learn how to apply analytical methods to real-world business problems, transforming data into actionable insights that drive strategic planning and operational improvements. The course will also explore contemporary applications of business analytics in industries such as marketing, finance, operations, and supply chain management, equipping students with the analytical skills essential for effective problem solving in todays data-driven business environment.
Recommended Textbook
Essentials of Business Analytics 1st Edition by Jeffrey D. Camm
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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) ______ is used in the pharmaceutical industry to assess the risk of introducing a new drug.
A) Data dashboards
B) Charts
C) Spreadsheet models
D) Simulation
Answer: D
Q3) Which of the following techniques is used in predictive analytics?
A) Data dashboards
B) Linear regression
C) Data visualization
D) Optimization models
Answer: B
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Chapter 2: Descriptive Statistics
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Sample Questions
Q1) The scores of a sample of students in a Math test are 20, 15, 19, 21, 22, 12, 17, 14, 24, 16 and in a Stat test are 16, 12, 19, 17, 22, 14, 20, 21, 24, 15, 13.
a. Compute the mean and median scores for both the Math and the Stat tests.
b. Compare the mean and median scores computed in part a. Comment.
Answer: a. For Math test:
Mean = 18.
Median = 18.
For Stat test:
Mean = 17.5.
Median = 17.
b. The mean and the median scores for statistics are lower than that for mathematics. These lower values are because of an additional score 13 for statistics which is lower than the mean and the median scores for mathematics.
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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) _____ merges maps and statistics to present data collected over different geographies.
A) The heat map
B) The geographic information system
C) A geographical map
D) The statistical information system
Answer: C
Q3) _____ helps in designing effective tables and charts for data visualization.
A) Data-ink ratio
B) Crosstabulation
C) PivotTable
D) Scatter charts
Answer: A
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Chapter 4: Linear Regression
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Sample Questions
Q1) _____ is used to test the hypothesis that the values of the regression parameters 1, 2, . . . , q are all zero.
A) An F test
B) A t test
C) The least squares method
D) Extrapolation
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) The prespecified value of the independent variable at which its relationship with the dependent variable changes in a piecewise linear regression model is referred to as the
A) milestone
B) breakpoint
C) tipping point
D) watchpoint
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Page 6
Chapter 5: Time Series Analysis and Forecasting
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Sample Questions
Q1) Causal models:
A) provide evidence of a causal relationship between an independent variable and the variable to be forecast.
B) use the average of the most recent data values in the time series as the forecast for the next period.
C) occur whenever all the independent variables are previous values of the same time series.
D) relate a time series to other variables that are believed to explain or cause its behavior.
Q2) Using a large value for order k in the moving averages method is effective in:
A) tracking changes in a time series more quickly.
B) smoothing out random fluctuations.
C) providing a more accurate forecast variable value.
D) eliminating the effect of seasonal variations in the time series.
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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Chapter 6: Data Mining
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Sample Questions
Q1) _____ 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
Q2) The data preparation technique used in market segmentation to divide consumers into different homogeneous groups is _____.
A) data visualization
B) cluster analysis
C) market analysis
D) supervised learning
Q3) Single linkage is a measure of calculating dissimilarity between clusters by:
A) considering only the two most dissimilar observations in the two clusters.
B) computing the average dissimilarity between every pair of observations between the two clusters.
C) considering only the two closest observations in the two clusters.
D) considering the distance between the cluster centroids.
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Chapter 7: Spreadsheet Models
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Sample Questions
Q1) The VLOOKUP with range set to _____ takes the first argument and searches the first column of the table for the last row that is strictly less than the first argument.
A) FALSE
B) TRUE
C) LESS
D) NULL
Q2) With reference to the SUMPRODUCT function, which of the following statements is true?
A) The range of cells for each array must contain only nonzero values.
B) Any cell that does not satisfy the specified given condition or criteria will not be considered.
C) The array appearing as the first argument must be sorted in ascending order.
D) The arrays that appear as arguments must be of the same dimension.
Q3) Navigation in a spreadsheet model can be facilitated by:
A) using different spreadsheets for each formula in the model.
B) using long calculations in the cells.
C) using clear labels and proper formatting and alignment.
D) referencing data by using hyperlinks to the problem statement.
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Chapter 8: Linear Optimization Models
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Sample Questions
Q1) The nonnegativity constraints create a feasible region that is:
A) unbound by the horizontal axis only.
B) an area with no point satisfying all the constraints.
C) symmetric about the vertical axis around the origin.
D) bound by the horizontal and vertical axes.
Q2) 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.
Q3) 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.
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Chapter 9: Integer Linear Optimization Models
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Sample Questions
Q1) Delisshious Toasty Chocolates Company largely produces two types of chocolate bars, Almond Tasty and Cashew Crunchy. The maintenance costs per day incurred to produce the two types of chocolate bars are $100 and $120, respectively. The manufacturing cost per chocolate bar is $2 for Almond Tasty and $2.5 for Cashew Crunchy. The daily production capacity of Almond Tasty and Cashew Crunchy chocolate bars are 1100 and 1250, respectively. There is only one machine to produce whichever type of chocolate bar will be produced that day. Only one type of bar can be made on a given day.
Let C = the number of Almond Tasty chocolate bars produced
C = the number of Cashew Crunchy chocolate bars are produced
Y = 1 if the machine produces Almond Tasty; 0, otherwise
Y = 1 if the machine produces Cashew Crunchy; 0, otherwise a. Write a constraint that sets the next day's maximum production of Almond Tasty to 1100.
b. Write a constraint that sets the next day's maximum production of Cashew Crunchy to 1250.
c. Write a constraint that requires that production be set up for exactly one of the two chocolates bars.
d. Write the cost function to be minimized.
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Chapter 10: Nonlinear Optimization Models
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Sample Questions
Q1) A global minimum
A) is also a local maximum.
B) need not be a local maximum, but vice versa is true.
C) is also a local minimum.
D) need not be local minimum, but vice versa is true.
Q2) Solving nonlinear problems with local optimal solutions is performed using _____, in Excel Solver, which is based on more classical optimization techniques.
A) Goal Seeker
B) Linear Regression
C) GRG Nonlinear
D) Simplex LP
Q3) A function that is bowl-shaped up is called a(n) _____ function.
A) concave
B) optimal
C) convex
D) elliptical
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Chapter 11: Monte Carlo Simulation
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Sample Questions
Q1) According to the _____, the sum of independent random variables can be approximated by a normal probability distribution.
A) what-if analysis
B) central limit theorem
C) simulation optimization approach
D) discrete-event simulation method
Q2) A _____ uses repeated random sampling to represent uncertainty in a model representing a real system and that computes the values of model outputs.
A) Monte Carlo simulation
B) what-if analysis
C) deterministic model
D) discrete event simulation
Q3) ASP cannot guarantee an optimal solution to a simulation optimization model because
A) the optimization problem will have only one local optimal solution due to the linear relationship.
B) of sampling error resulting from nonlinear relationships.
C) it is not possible to compare solutions across runs.
D) of sampling error resulting from the presence of the random variables.
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Page 13
Chapter 12: Decision Analysis
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Sample Questions
Q1) An intersection or junction point of a decision tree is called a(n) _____.
A) node
B) stem
C) intercept
D) branch
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) _____ are possible outcomes for chance events that affect the consequences associated with a decision alternative.
A) Payoffs
B) Forecasts
C) Decision trees
D) States of nature
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