Data-Driven-Decision-Making認證考試的新考古題匯總

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最新的 Courses and Certificates Data-Driven-Decision-Making 免費考試真題 (Q91-Q96):

問題 #91
A school board has nine voting members. Five members need to be chosen each year for the finance committee. Why should the combination technique be used when selecting committee members?

答案：C

解題說明：
The combination technique is appropriate when selecting items or people from a group and the order of selection does not matter. In this case, five members are being chosen from nine voting members to serve on the finance committee. What matters is which five individuals are selected, not the sequence in which their names are chosen. Combinations are used precisely for this type of situation because they count unique groups without regard to arrangement. If order did matter, then a permutation approach would be required instead. The options referring to correlation and meeting attendance are unrelated to the mathematical reason for using combinations. This is a straightforward committee-selection problem, which is one of the most common applications of combinations in probability and counting methods. Recognizing whether order matters is the essential step in choosing between combinations and permutations. Since a finance committee is defined by its membership rather than by the order in which members were picked, the correct answer is that the selection order of committee members is not important.


問題 #92
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?

答案：C

解題說明：
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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問題 #93
What results from starting an analysis with flawed data?
Choose 2 answers.

答案：B,D

解題說明：
Starting an analysis with flawed data significantly undermines the effectiveness of data-driven decision making. One major consequence is that more 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 that missing 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 are B and D.


問題 #94
A researcher notes that people who exercise daily tend to sleep better. The researcher then asks subjects to keep a sleep diary and record the number of hours they sleep each night. Some diaries have few entries, but the subjects claim they are well rested. Which type of error is represented in this research?

答案：C

解題說明：
This scenario illustrates response bias because the quality and completeness of the recorded responses are questionable. The researcher depends on subjects to accurately document their sleeping hours in diaries, yet some subjects submit few entries while still claiming they are well rested. This creates a mismatch between documented evidence and self-reported perception. Response bias occurs when participants provide answers that do not fully or accurately reflect reality, whether intentionally or unintentionally. In this case, the subjects may be estimating, omitting information, or reporting what they believe sounds acceptable rather than what was consistently recorded. The problem is not mainly lack of blinding, since there is no indication that concealed treatment assignment is relevant. It is also not primarily cause-and-effect confusion, because the issue described concerns the reliability of the reported data rather than drawing a causal conclusion.
Conscious bias is less fitting because the question points to flawed responses rather than deliberate manipulation by the researcher. Therefore, the best answer is response bias, as the data collected from subjects may not accurately represent their actual sleep behavior.


問題 #95
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?

答案：B

解題說明：
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.


問題 #96
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