[Jun-2026] Data-Driven-Decision-Making Free Sample Questions to Practice One Year Update
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NEW QUESTION # 17
Which type of analytics classification uses experimental design and optimization to suggest a course of action?
- A. Predictive analytics
- B. Descriptive analytics
- C. Prescriptive analytics
- D. Diagnostic analytics
Answer: C
Explanation:
Prescriptive analyticsis the analytics classification that uses experimental design and optimization techniques to suggest a specific course of action. In data-driven decision making, prescriptive analytics represents the most advanced stage of analytics, as it not only predicts outcomes but also recommends decisions that lead to optimal results.
Descriptive analytics summarizes historical data to explain what has already happened, while predictive analytics uses statistical and probabilistic models to estimate what is likely to happen in the future. Diagnostic analytics focuses on understanding why something happened by identifying root causes. In contrast, prescriptive analytics answers the critical question:what should be done.
Prescriptive analytics relies on methods such as optimization models, simulation, decision trees, and experimental design. These techniques evaluate multiple scenarios, constraints, and objectives to identify the best possible action. For example, organizations use prescriptive analytics to optimize pricing, allocate resources efficiently, schedule operations, or determine optimal investment strategies.
Within data-driven decision-making frameworks, prescriptive analytics bridges analysis and action by directly supporting managerial decision-making. It transforms analytical insights into concrete recommendations that can be implemented to improve performance and outcomes. Therefore, the correct answer isC, as prescriptive analytics explicitly uses experimental design and optimization to suggest a course of action.
NEW QUESTION # 18
Which type of analysis determines whether there was a significant difference in the average donor solicitation amount between three nonprofit hospital events?
- A. Logistic regression
- B. Time series
- C. ANOVA
- D. Cluster
Answer: C
Explanation:
Analysis of Variance (ANOVA)is used to compare the means of three or more groups to determine whether statistically significant differences exist. In data-driven decision making, ANOVA is appropriate when evaluating differences across multiple categories.
In this scenario, the analyst is comparing average donor solicitation amounts across three separate events.
ANOVA tests whether at least one group mean differs from the others.
Cluster analysis groups data, time series examines trends over time, and logistic regression predicts categorical outcomes. Therefore, the correct answer isD, ANOVA.
NEW QUESTION # 19
A political ballot gives voters the option to vote for one of three candidates. Eight voters cast their ballots.
Which statistical rule should be used to determine the possible voting outcomes?
- A. Bayes' theorem
- B. Multiplication principle
- C. Conditional probability
- D. Combination
Answer: B
Explanation:
Themultiplication principleis used to determine the number of possible outcomes when multiple independent choices occur in sequence. In data-driven decision making and probability theory, this rule applies when each event has a fixed number of outcomes and each outcome is independent of the others.
In this scenario, each of the eight voters can independently choose one of three candidates. The total number of possible voting outcomes is calculated by multiplying the number of choices available for each voter.
Because the voters act independently and order matters in counting outcomes, the multiplication principle is the correct method.
Conditional probability applies when outcomes depend on prior events, Bayes' theorem updates probabilities based on new information, and combinations are used when order does not matter. None of these fit the structure of this problem.
Therefore, the correct answer isA, multiplication principle.
NEW QUESTION # 20
How do analytics help an organization?
- A. They develop fact-based strategies.
- B. They increase employees' use of information systems.
- C. They assist with investment management.
- D. They use data to persuade consumers.
Answer: A
Explanation:
Analytics help organizations primarily by enabling the development offact-based strategies, which is a central principle of data-driven decision making. Rather than relying on intuition, assumptions, or anecdotal evidence, analytics allows organizations to systematically analyze data to understand performance, identify opportunities, manage risks, and support strategic decisions.
Through descriptive analytics, organizations gain insight into historical performance andoperational efficiency. Predictive analytics enables them to anticipate future trends, customer behavior, and potential outcomes. Prescriptive analytics further supports decision-making by recommending optimal actions under various constraints. Together, these approaches transform raw data into actionable insights that guide strategic planning and execution.
While analytics may support investment management, marketing, or information systems usage, these are specific applications, not the fundamental organizational benefit. Analytics is not primarily used to persuade consumers, nor is its main objective to increase system usage among employees. Instead, its value lies in improving decision quality by grounding strategies in empirical evidence.
In data-driven decision-making frameworks, analytics serves as a structured approach to aligning data, models, and business objectives. By developing strategies based on verified data and analytical methods, organizations reduce uncertainty, improve performance, and gain competitive advantage. Therefore, the correct answer isC, as analytics enable organizations to developfact-based strategies.
NEW QUESTION # 21
Two project teams are assigned to upgrade an on-premise data warehouse to a cloud-based data lake in 13 months. The infrastructure team has five team members, while the enterprise analytics team has three team members. The enterprise analytics team cannot move into production until the infrastructure team has completed the migration.
What should be used to find the probability that the project will be completed on time?
- A. Bayes' theorem
- B. Conditional probability
- C. Multiplication principle
- D. Combination
Answer: B
Explanation:
This scenario requires the use of **conditional probability**, which applies when the likelihood of one event depends on the occurrence of another event. In data-driven decision making, conditional probability is used to model dependent events within processes, workflows, and project timelines.
In this case, the enterprise analytics team's ability to move into production is **dependent on** the infrastructure team completing the migration. Because one event cannot occur unless another event has already occurred, the probability of completing the project on time must account for this dependency.
The multiplication principle applies to independent events, Bayes' theorem updates probabilities based on new information, and combinations are used for counting outcomes, not dependency analysis. Conditional probability explicitly captures the relationship between dependent tasks.
Project risk analysis and scheduling often rely on conditional probability to assess completion likelihood when tasks are sequentially linked. Therefore, the correct answer is **C**, conditional probability.
NEW QUESTION # 22
Which graphical display is used to examine the distribution of a data set with quartiles?
- A. Pareto chart
- B. Scatterplot
- C. Boxplot
- D. Bivariate chart
Answer: C
Explanation:
Aboxplotis specifically designed to display the distribution of a dataset using quartiles. In data-driven decision making, boxplots visually summarize data through the minimum, first quartile, median, third quartile, and maximum.
Boxplots are useful for identifying spread, central tendency, skewness, and potential outliers. Scatterplots and bivariate charts analyze relationships between variables, while Pareto charts rank categorical data by frequency.
Because quartiles are the defining feature of a boxplot, the correct answer isC.
NEW QUESTION # 23
A retail manager collected the following sales-receipt totals from the store's cashiers:
$25, $22, $48, $42, $32, $28, $24, $54, $34, $41, $48
What is the median of this sales-receipt data?
- A. $48
- B. $41
- C. $34
- D. $25
Answer: C
Explanation:
Themedianis the middle value of a dataset when the data is arranged in ascending order. It is a key descriptive statistic used in data-driven decision making because it is resistant to extreme values.
First, sort the data in ascending order:
22, 24, 25, 28, 32,34, 41, 42, 48, 48, 54
There are 11 values in total, so the median is the 6th value. The 6th value is$34, making it the median.
The median provides insight into the typical transaction size without being influenced by unusually large receipts. Therefore, the correct answer isB.
NEW QUESTION # 24
A financial analyst theorizes that commute times increase as the percentage of land availability for homes in a city decreases. To test this hypothesis, the analyst uses a regression analysis to explore how land availability predicts commute time.
What does land availability represent in this regression?
- A. It is the dependent variable.
- B. It is the independent variable.
- C. It is the target variable.
- D. It is a control.
Answer: B
Explanation:
In regression analysis, theindependent variableis the predictor used to explain or estimate changes in another variable. In data-driven decision making, identifying the correct variable roles is essential for meaningful interpretation.
In this scenario, land availability is used to predict commute time. Commute time is the outcome being explained, making it the dependent or target variable. Land availability influences or explains changes in commute time, which makes it theindependent variable.
Controls are additional variables included to isolate effects, but land availability is the primary predictor of interest. Therefore, optionCis correct.
NEW QUESTION # 25
A manager has been assigned to manage a digital marketing analytics team. The manager tasks the team with determining similarities among existing customers in the company's database, such as similarities in products purchased, location, and the average amount spent per order among existing customers.
Which type of activity will help the team accomplish this task?
- A. Touchpoint analysis
- B. Linear programming
- C. Data mining
- D. Regression analysis
Answer: C
Explanation:
Data miningis the appropriate activity for identifying patterns, similarities, and relationships within large datasets. In data-driven decision making, data mining techniques such as clustering and association analysis are commonly used to segment customers based on behavior and characteristics.
The task described involves uncovering hidden patterns across multiple variables, which aligns directly with data mining objectives. Linear programming focuses on optimization, regression predicts outcomes, and touchpoint analysis examines customer interactions rather than similarities.
Therefore, the correct answer isA, data mining.
NEW QUESTION # 26
Which analytic used in healthcare is calculated as a proportion of new cases compared to person-time units?
- A. Cumulative incidence
- B. Morbidity rate
- C. Prevalence
- D. Incidence rate
Answer: D
Explanation:
Theincidence rateis a healthcare analytic calculated as the number ofnew casesof a condition divided by person-time units at risk. In data-driven decision making, this metric is essential for understanding how quickly new cases occur within a population over time.
Person-time accounts for both the number of individuals and the duration they are observed, making the incidence rate particularly useful when populations are dynamic or when observation periods vary. This distinguishes incidence rate from cumulative incidence, which measures new cases over a fixed population and time period without person-time adjustment.
Prevalence measures existing cases at a point in time, and morbidity is a broader term describing illness burden rather than a specific rate calculation.
Because the question explicitly referencesnew cases compared to person-time units, the correct answer isB, incidence rate.
NEW QUESTION # 27
For which situation could a scatter diagram be used?
- A. Demonstrating a visual precedence of a prioritization matrix
- B. Demonstrating a significant difference between the means of two groups of data
- C. Demonstrating a relationship between variables
- D. Demonstrating a significant difference between the frequencies of two groups of data
Answer: C
Explanation:
Ascatter diagramis used to visually examine therelationship between two quantitative variables. In data- driven decision making, scatter diagrams help analysts assess whether variables move together, whether the relationship is positive, negative, or nonexistent, and whether the relationship appears linear or nonlinear.
Each point on a scatter diagram represents a paired observation of two variables, such as advertising spend and sales revenue or hours studied and test scores. Patterns in the plotted points can suggest correlation, which may later be explored using regression analysis. Scatter diagrams are exploratory tools and do not, by themselves, establish causation.
A prioritization matrix ranks options, frequency differences are examined using bar or Pareto charts, and differences in means are evaluated using hypothesis tests such as t-tests or ANOVA. Therefore, the correct application of a scatter diagram is to demonstraterelationships between variables, making optionBcorrect.
NEW QUESTION # 28
A county government is creating a budget for the next fiscal year. They wish to use analytics to guide their decisions about costs.
Which analytic method can the county apply to this issue?
- A. Median cost for all county projects
- B. Average number of projects completed
- C. Median number of projects completed last year
- D. Average cost per project spent by other similar counties
Answer: D
Explanation:
To guide budgeting decisions, data-driven decision making emphasizesbenchmarking against comparable organizations. Using theaverage cost per project spent by other similar countiesallows the county to assess whether its planned expenditures are reasonable and competitive.
Benchmarking provides external context that internal historical metrics cannot. While median costs or project counts describe internal performance, they do not indicate whether spending levels are appropriate relative to peers. Comparing average costs across similar counties helps identify inefficiencies, cost-saving opportunities, and realistic budget targets.
Therefore, optionAis the most effective analytic method for cost-based decision-making in this scenario.
NEW QUESTION # 29
A healthcare organization implements a campaign to improve patient satisfaction during recent stays. The average patient satisfaction before the campaign is M = 4.20, SD = 3.0. Six months after the new campaign, the average patient satisfaction is M = 1.5, SD = 2.0.
Which action should the hospital management team take?
- A. Continue the campaign because patient satisfaction significantly increased from baseline to six months following the campaign introduction
- B. Continue the campaign because there was an increase in patients that came to the hospital during the six months
- C. Change the campaign because it worked initially but is no longer effective
- D. Discontinue the campaign because patient satisfaction declined from baseline to six months following the campaign introduction
Answer: D
Explanation:
Data-driven decision making requires comparing outcomes before and after an intervention to assess effectiveness. In this scenario, the mean patient satisfaction scoredeclined from 4.20 to 1.5following implementation of the campaign, indicating a substantial decrease in satisfaction.
Despite the reduced standard deviation, the large drop in the mean suggests the campaign did not achieve its intended goal and may have negatively affected patient experience. Continuing or modifying the campaign is not justified without evidence of initial improvement or external factors explaining the decline.
Management decisions must be grounded in outcome data rather than assumptions or unrelated metrics such as patient volume. Ethical and effective use of statistics requires discontinuing interventions that demonstrably worsen outcomes.
Therefore, the correct action is todiscontinue the campaign, making optionAthe correct answer.
NEW QUESTION # 30
A boutique specializing in gifts reviews its sales data over the last year. It observes a slow decline in revenue in the first quarter, a growth in revenue in the second quarter, a slight decline in revenue in the third quarter, and a rapid increase in revenue in the fourth quarter.
Which data pattern type can the sales data be assessed against?
- A. Cyclicality
- B. Seasonality
- C. Random variation
- D. Irregularity
Answer: B
Explanation:
Seasonalityrefers to predictable patterns in data that repeat at regular intervals, such as quarters or months, due to seasonal factors. In data-driven decision making, identifying seasonal patterns helps organizations forecast demand and plan operations.
The boutique's revenue shows distinct quarterly patterns: declines and increases that align with different times of the year. The sharp increase in the fourth quarter is especially indicative of seasonal effects, such as holiday shopping.
Random variation and irregularity describe unpredictable fluctuations, while cyclicality refers to long-term economic cycles rather than recurring annual patterns. Therefore, the correct answer isC, seasonality.
NEW QUESTION # 31
A researcher seeks to pass a bond issue and asks a sample of respondents who have a bachelor's degree if they are voting in favor of the bond because it would be beneficial to the county.
Which type of error does this represent?
- A. Confusion of association and causality
- B. Response bias
- C. Faulty operationalization
- D. Selection bias
Answer: D
Explanation:
This scenario represents **selection bias**, which occurs when a sample is not representative of the population being studied. In data-driven decision making, valid conclusions depend on collecting data from a sample that accurately reflects the broader population.
By surveying only respondents with a bachelor's degree, the researcher systematically excludes other segments of the population who may have different opinions about the bond issue. Educational attainment may influence voting behavior, making the sample biased toward a particular viewpoint. As a result, the findings cannot be generalized to the entire voting population.
While the wording of the question may be persuasive, the primary statistical error is the **non-random and restricted selection of respondents**. Response bias relates to how participants answer questions, whereas this issue arises before responses are even collected. Faulty operationalization and confusion of causality are not applicable here.
Data-driven decision making stresses ethical sampling practices to avoid misleading conclusions. Therefore, the correct answer is **D**, selection bias.
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NEW QUESTION # 32
What classifies analytics as descriptive, predictive, or prescriptive?
- A. The sample size and analysis technique used
- B. The purpose and methods
- C. The kind of software used for the analysis
- D. The data validity and reliability
Answer: B
Explanation:
Analytics is classified as descriptive, predictive, or prescriptive based onthe purpose of the analysis and the methods used to carry it out, which is a foundational concept in data-driven decision making. The distinction reflects the type of managerial question being addressed rather than technical aspects such as software tools, sample size, or data reliability.
Descriptive analytics focuses on understandingwhat has happenedby summarizing historical data. It relies on descriptive statistics, reports, dashboards, and data visualizations to provide insights into past performance.
Predictive analytics extends this approach to determinewhat is likely to happenby using statistical models, probability distributions, regression analysis, and forecasting techniques to estimate future outcomes.
Prescriptive analytics goes further by identifyingwhat should be doneto achieve desired results. It uses optimization models, decision trees, simulations, and scenario analysis to recommend the best course of action under given constraints.
In data-driven decision making, the classification of analytics depends on how results are intended to support decisions and the analytical techniques applied to achieve that goal. Factors such as data quality and software influence accuracy and efficiency but do not define the analytics category itself. Therefore, the correct classification criterion is thepurpose and methods, making optionCthe correct answer.
NEW QUESTION # 33
Amusement Park W is in California. Amusement Park X is in Texas. A survey asks 1,000 people living in California if they prefer Amusement Park W or X.
Which problem exists with this survey?
- A. Information bias
- B. Random error
- C. Systematic error
- D. Measurement bias
Answer: C
Explanation:
The primary problem with this survey issystematic error, which occurs when the data collection process consistently favors certain outcomes due to flawed design. In data-driven decision making, systematic error arises when a sampling method introduces bias that skews results in a predictable direction.
In this scenario, surveying only people living in California creates a location-based bias. Respondents are far more likely to prefer Amusement Park W because it is geographically closer, more familiar, and more accessible than Amusement Park X in Texas. This bias does not occur randomly; instead, it systematically influences responses toward one option, making the results unreliable for comparing overall preferences between the two parks.
Random error would involve unpredictable variation, which is not the issue here. Measurement bias relates to how questions are asked or measured, and information bias concerns inaccurate or misleading data reporting.
The core issue is thenon-representative sample, which violates the principle of unbiased data collection.
Data-driven decision making emphasizes that valid conclusions require representative samples. Because the survey design inherently favors one outcome, the results cannot be generalized, makingsystematic errorthe correct answer.
NEW QUESTION # 34
What is a disadvantage of using a balanced scorecard?
- A. It is expensive to implement effectively within an organization's operations.
- B. It does not link operations with company strategy.
- C. It does not include a mix of financial and nonfinancial performance measures.
- D. It requires time and effort to develop a meaningful template.
Answer: D
Explanation:
A key disadvantage of using abalanced scorecardis that itrequires significant time and effort to develop a meaningful and effective template. In data-driven decision making, the value of a balanced scorecard depends on careful selection of performance measures that align with organizational strategy.
Developing a balanced scorecard involves defining strategic objectives, selecting appropriate metrics, setting targets, and ensuring data availability. This process can be resource-intensive, especially in large or complex organizations. However, once implemented, the balanced scorecard offers substantial long-term benefits.
The other options are incorrect because the balanced scorecard explicitly includes both financial and nonfinancial measures and is designed to link operations with strategy. While implementation may involve some cost, expense alone is not typically cited as its primary disadvantage.
Therefore, the correct answer isA.
NEW QUESTION # 35
Which performance metric simultaneously accounts for financial, customer, internal process, and learning metrics?
- A. Balance sheet
- B. Balanced scorecard
- C. Income statement
- D. Customer complaint report
Answer: B
Explanation:
Thebalanced scorecard (BSC)is a performance management framework that simultaneously accounts for financial, customer, internal process, and learning and growth metrics. In data-driven decision making, the balanced scorecard provides a holistic view of organizational performance rather than focusing on a single dimension of success.
Financial metrics assess profitability and sustainability, customer metrics evaluate satisfaction and loyalty, internal process metrics examine operational efficiency, and learning and growth metrics focus on employee development and innovation. By integrating these perspectives, the balanced scorecard ensures alignment between day-to-day operations and long-term strategic goals.
Customer complaint reports, income statements, and balance sheets each address only one aspect of performance. They do not provide the multi-dimensional insight necessary for strategic decision-making.
Therefore, the correct answer isA, balanced scorecard.
NEW QUESTION # 36
In an experimental study, researchers are testing a new flea preventive medication on dogs using a blind study. Dogs are treated with the new medication or with a placebo.
Who should know which dogs are given the medication or the placebo for this blind study?
- A. Neither the researchers nor the dog owners nor the response gatherers
- B. Only the researchers
- C. Only the dog owners
- D. The researchers, the dog owners, and the response gatherers
Answer: B
Explanation:
In ablind study, the purpose is to reduce bias that may influence responses or outcomes. In data-driven decision making, a blind study is designed so thatsubjects and response gatherers do not knowwhich treatment is administered, while the researchers do retain this information to correctly manage and analyze the experiment.
In this scenario, dog owners and response gatherers should not know whether the dogs received the medication or a placebo, as this knowledge could influence reporting of outcomes or observations. However, researchers must know which treatment each dog receives to ensure proper administration, monitoring, and statistical analysis.
If neither researchers nor participants knew the assignments, the study would be classified as adouble-blind study, which is not stated here. Allowing owners or response gatherers to know treatment assignments would introduce bias and undermine experimental validity.
Therefore, in a blind study,only the researchersshould know which dogs received the medication or placebo, making optionCthe correct answer.
NEW QUESTION # 37
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