Data-Driven-Decision-Making Exams Dumps, Data-Driven-Decision-Making Most Reliable Questions

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WGU VPC2Data-Driven Decision MakingC207 Sample Questions (Q101-Q106):

NEW QUESTION # 101
Which tool is often referred to as a fishbone chart or diagram?

Answer: B

Explanation:
Thecause-and-effect diagram, also known as thefishbone diagramorIshikawa diagram, is used to identify potential causes of a problem. In data-driven decision making, it helps teams systematically explore root causes rather than focusing on symptoms.
The diagram visually organizes possible causes into categories such as people, processes, materials, machines, and environment. Histograms show distributions, flowcharts depict process steps, and scatter diagrams show relationships between variables.
Therefore, the correct answer isC, cause-and-effect diagram.


NEW QUESTION # 102
What is the purpose of linking strategy to performance assessment in an organization?

Answer: A

Explanation:
Linking strategy to performance assessment helps an organization define where it needs or desires to be and measure progress toward that target. This connection is essential because it ensures that performance metrics are not selected in isolation, but instead support the mission, goals, and priorities of the organization. When strategy and assessment are aligned, managers can evaluate whether operational efforts are contributing to desired outcomes, identify gaps between current and expected performance, and make better-informed decisions about improvement. The other options do not reflect the main purpose. Increasing data collection may occur, but it is not the central reason for linking strategy to assessment. Reducing action plans is not a valid objective, and translating the mission only for team players is too narrow and inaccurate. Strategic performance assessment creates direction, accountability, and clarity across the organization. Therefore, the correct answer is that it provides a target of where an organization needs or desires to be.


NEW QUESTION # 103
A clothing company wants to predict sales figures based on the amount spent on advertising.
Which type of regression analysis should this company use?

Answer: D

Explanation:
When predicting a continuous outcome based on a single predictor, data-driven decision making recommends simple linear regression. In this case, sales figures are continuous, and advertising spend is a single explanatory variable.
Linear regression models the relationship between one independent variable and one dependent variable by estimating a straight-line relationship. Time series regression is used when data are indexed over time, logistic regression is used for binary outcomes, and multiple linear regression requires multiple predictors.
Because the company is using only advertising spend to predict sales,linear regressionis the most appropriate method. Therefore, the correct answer isB.


NEW QUESTION # 104
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: D

Explanation:
TheCheckphase 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 isA, Check.


NEW QUESTION # 105
What results from starting an analysis with flawed data?
Choose 2 answers.

Answer: A,D

Explanation:
Starting an analysis with flawed data significantly undermines the effectiveness of data-driven decision making. One major consequence is thatmore time is spent managing data than analyzing data. Analysts must devote substantial effort to cleaning, validating, and correcting errors before meaningful analysis can occur, delaying insights and increasing costs.
Another critical result is thatmissing data tend to skew the results of the analysis. Incomplete data can distort averages, trends, and statistical relationships, leading to biased conclusions and unreliable decisions.
This is especially problematic in predictive and inferential analytics, where assumptions about data completeness are essential.
Using spreadsheets or placing data in charts does not inherently result from flawed data, nor does it resolve data quality issues. While visualization can help identify errors, it is not a direct outcome of starting with flawed data.
Data-driven decision making emphasizes that poor-quality input leads to poor-quality output. Ensuring data accuracy and completeness before analysis is essential for producing valid insights. Therefore, the correct answers areB and D.


NEW QUESTION # 106
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