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Data-Driven-Decision-Making New Study Materials | Updated Data-Driven-Decision-Making Demo

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WGU VPC2Data-Driven Decision MakingC207 Sample Questions (Q30-Q35):

NEW QUESTION # 30
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. $34
B. $25
C. $48
D. $41

Answer: A

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 # 31
For which situation could a scatter diagram be used?

A. Demonstrating a relationship between variables
B. Demonstrating a significant difference between the frequencies of two groups of data
C. Demonstrating a significant difference between the means of two groups of data
D. Demonstrating a visual precedence of a prioritization matrix

Answer: A

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 # 32
Which two results occur when the null hypothesis is accepted using an F-test?
Choose 2 answers.

A. The test statistic is greater than the critical value.
B. The test statistic is less than the critical value.
C. There appears to be no difference between the two samples.
D. There appears to be a difference between the two samples.

Answer: B,C

Explanation:
When the null hypothesis is accepted in anF-test, it indicates that there is no statistically significant difference between group variances or means, depending on the test design. Acceptance occurs when thetest statistic is less than the critical value, meaning the observed variation is within expected limits.
Accepting the null hypothesis implies thatno meaningful differenceexists between the samples. If the test statistic exceeded the critical value, the null hypothesis would be rejected.
Thus, the correct results areA and D.

NEW QUESTION # 33
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 number of projects completed last year
B. Median cost for all county projects
C. Average cost per project spent by other similar counties
D. Average number of projects completed

Answer: C

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 # 34
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. Systematic error
B. Random error
C. Information bias
D. Measurement bias

Answer: A

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 # 35
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