Business Data Mining Question
Bank
Course Introduction
Business Data Mining explores the techniques and applications of extracting actionable insights from large sets of business data. This course covers fundamental data mining processes such as data preprocessing, classification, clustering, association rule mining, and predictive modeling. Students learn to use analytical tools and software to discover patterns and trends within real-world business datasets, supporting strategic decision-making. Emphasis is placed on interpreting results, evaluating model performance, and understanding the ethical considerations associated with data mining in contemporary business environments. Practical case studies and hands-on projects reinforce the application of data mining techniques in marketing, finance, operations, and other business domains.
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) Tactical decisions define:
A) the day-to-day activities of the organization.
B) the goals and plans of the organization.
C) the domain of operations managers, who are close to the customer.
D) the steps taken to achieve the goals and objectives.
Answer: D
Q2) ______ assigns values to outcomes based on the decision maker's attitude toward risk, loss, and other factors.
A) Simulation optimization
B) Utility theory
C) Optimization model
D) Data dashboard
Answer: B
Q3) All the three descriptive, predictive, and prescriptive analytics are used in:
A) Marketing and HR analytics.
B) Marketing and Health Care analytics.
C) Health Care and HR analytics.
D) Health Care and Financial analytics.
Answer: B
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Page 3
Chapter 2: Descriptive Statistics
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Sample Questions
Q1) Compute the mean of the following data: 56 42 37 29 45 51 30 25 34 57
A) 42.8
B) 52.1
C) 40.6
D) 39.4
Answer: C
Q2) In a(n) _____, one or more variables are identified and controlled or manipulated so that data can be obtained about how they influence the variable of interest identified first.
A) experimental study
B) observational study
C) categorical study
D) variable study
Answer: A
Q3) A variable whose values are not known with certainty is called a _____.
A) certain variable
B) random variable
C) constant variable
D) decision variable
Answer: B
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Chapter 3: Data Visualization
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Sample Questions
Q1) In designing an effective table,
A) avoid the use of unnecessary ink in tables.
B) increase the number of horizontal and vertical lines in the table.
C) avoid the use of necessary ink in tables.
D) do not focus on the alignment of the text and numbers in the table.
Answer: A
Q2) A line chart that has no axes but is used to provide information on overall trends for time series data is called a
A) time series plot.
B) sparkline.
C) trendline.
D) bubble chart.
Answer: B
Q3) The best way to differentiate chart elements is using A) too many colors.
B) labels.
C) bubbles.
D) chart titles.
Answer: B
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Page 5
Chapter 4: Linear Regression
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Sample Questions
Q1) What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89?
A) 31.89
B) 19.32
C) 18.43
D) 15.32
Q2) The process of making conjecture about the value of a population parameter, collecting sample data that can be used to assess this conjecture, measuring the strength of the evidence against the conjecture that is provided by the sample, and using these results to draw a conclusion about the conjecture is better known as:
A) postulation.
B) hypothesis testing.
C) statistical inference.
D) empirical research.
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6
Chapter 5: Time Series Analysis and Forecasting
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Sample Questions
Q1) 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.
Q2) _____ 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
Q3) In the moving averages method, the order k determines the:
A) error tolerance
B) compensation for forecasting error
C) number of time series values under consideration
D) number of samples in each unit time period
Q4) Trends result from:
A) rapidly-arising short-term factors.
B) rapidly-arising long-term factors.
C) slowly-varying short-term factors.
D) slowly-varying long-term factors.
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Chapter 6: Data Mining
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Sample Questions
Q1) Jaccard's coefficient is different from the matching coefficient in that the:
A) former measures overlap while the latter measures dissimilarity.
B) former does not count matching zero entries while the latter does.
C) former deals with categorical variable while the latter deals with continuous variables.
D) former is affected by the scale used to measure variables while the latter is not.
Q2) _____ is a measure of calculating dissimilarity between clusters by considering only the two most dissimilar observations in the two clusters.
A) Single linkage
B) Complete linkage
C) Average linkage
D) Average group linkage
Q3) The estimation of the value for a continuous outcome is done during _____.
A) classification
B) prediction
C) data preparation
D) data sampling
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Chapter 7: Spreadsheet Models
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Sample Questions
Q1) The _____ function allows the user to pull a subset of data from a larger table of data based on some criterion.
A) VLOOKUP
B) IF
C) SUMIF
D) COUNTIF
Q2) An electronics store sells two models of television. The sales of these two models, X and Y, are dependent, that is, if the price of one increases, the demand for the other increases. A study is made to find the relationship between the demand (D) and the price (P) in order to maximize the revenue from these products. The result of the study is shown below:
DX = 476 - 0.54 PX + 0.22 PY
DY = 601 + 0.12 PX - 0.54 PY a. Construct a model for the total revenue and implement it on a spreadsheet.
b. Develop a two-way data table to estimate the optimal prices of each of the two products in order to maximize the total revenue. Vary price of each product from $600 to $900 in increments of $50.
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Chapter 8: Linear Optimization Models
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Sample Questions
Q1) 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.
Q2) Reference - 8.1. Restrictions on the type of permissible investments would be a _____ in this case.
A) feasible solution
B) surplus variable
C) slack variable
D) constraint
Q3) The change in the optimal objective function value per unit increase in the right-hand side of a constraint is given by the _____.
A) objective function coefficient
B) shadow price
C) restrictive cost
D) right-hand side allowable increase
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Chapter 9: Integer Linear Optimization Models
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Sample Questions
Q1) The following questions refer to an advertisement budgeting problem involving printing of five magazines represented by binary variables M1, M2, M3, M4, and M5.a.
Write a constraint modeling a situation in which two of the magazines M1, M4, and M5 must be printed.
b. Write a constraint modeling a situation in which, if M2 or M3 is printed, they must both be printed.
c. Write a constraint modeling a situation in which magazine M1 or M3 must be printed, but not both.
d. Write constraints modeling a situation where M2 cannot be printed unless magazine M3 and M5 also are printed.
e. Write a constraint in which not more than 4 of all the five magazines have to be printed.
f. Write a constraint in which exactly five of the magazines are printed.
Q2) Reference - 9.1. Pink, green, and black will be _____ of the color attribute.
A) levels
B) constraints
C) regression constants
D) utility values
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Chapter 10: Nonlinear Optimization Models
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Sample Questions
Q1) A feasible solution is _____ if there are no other feasible points with a smaller objective function value in the entire feasible region.
A) a global minimum
B) not a local maximum
C) not a local minimum
D) bowl-shaped
Q2) In the Bass forecasting model, parameter m:
A) measures the likelihood of adoption due to a potential adopter being influenced by someone who has already adopted the product.
B) measures the likelihood of adoption, assuming no influence from someone who has already adopted the product.
C) refers to the number of people estimated to eventually adopt the new product.
D) refers to the number of people who have already adopted the new product.
Q3) The reduced gradient is analogous to the _____ for linear models.
A) binary variable
B) binding constraint
C) reduced cost
D) objective coefficient
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12
Chapter 11: Monte Carlo Simulation
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Sample Questions
Q1) In a _____, a random variable can take any value in a specified range.
A) discrete probability distribution
B) cumulative distribution
C) relative frequency distribution
D) continuous probability distribution
Q2) In a(n) _____ relationship between two quantities, either one quantity never increases as the other increases, or one quantity never decreases as the other increases.
A) monotonic
B) random
C) classified
D) independent
Q3) _____ is the process of determining that a simulation model provides an accurate representation of a real system.
A) Regression
B) Verification
C) Consideration
D) Validation
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Chapter 12: Decision Analysis
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Sample Questions
Q1) The weighted average of the payoffs for a chance node is known as the_____.
A) median value
B) variance of the node
C) risk measure
D) expected value
Q2) A _____ is a decision maker who would choose a guaranteed payoff over a lottery with a better expected payoff.
A) risk taker
B) risk-neutral
C) risk avoider
D) risk-creator
Q3) Which of the following is true of decision trees when used to solve a complex problem?
A) They provide a useful way to decompose the problem.
B) They are used to compute a decision maker's risk tolerance.
C) They can be converted into truth tables.
D) They can be used only when the decision maker is risk neutral.
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