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Which step in the plan-do-check-act cycle is described as analyzing the results of an experiment and deciding whether those results can be improved?
Answer : A
The Check phase of the Plan-Do-Check-Act (PDCA) cycle involves evaluating outcomes and analyzing results. In data-driven decision making, this step compares actual performance against expected results to determine whether objectives were met.
During the Check phase, organizations review data, assess variation, and identify opportunities for improvement. Planning defines objectives, Doing implements changes, and Acting standardizes or adjusts processes based on evaluation.
Therefore, the correct answer is A, Check.
Which type of analysis determines whether there was a significant difference in the average donor solicitation amount between three nonprofit hospital events?
Answer : D
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 is D, ANOVA.
Why would a human resources department use both mean and median when doing a salary evaluation of a department?
Answer : C
Using both mean and median helps identify outliers, such as very high executive salaries that skew the average. A large difference between the two indicates uneven distribution.
Thus, the correct answer is C.
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?
Answer : C
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.
How does a balanced scorecard (BSC) differ from a key performance indicator (KPI)?
Answer : A
A key performance indicator (KPI) measures performance in a single critical area, such as revenue growth or customer satisfaction. In contrast, a balanced scorecard (BSC) provides a multi-dimensional view of organizational performance, typically across financial, customer, internal process, and learning perspectives.
Data-driven decision making emphasizes that relying on a single metric can lead to incomplete or biased conclusions. The BSC addresses this by integrating multiple KPIs into a cohesive framework aligned with strategic objectives.
Therefore, option A correctly explains the distinction between a KPI and a BSC.
