Free WGU Data-Driven-Decision-Making Practice Exam with Questions & Answers | Set: 2

In anormal distribution, data is symmetrically distributed around the center, causing the mean and median to be approximately equal. This is a fundamental property emphasized in data-driven decision making.

Skewed distributions, such as Pareto, cause the mean and median to differ significantly. Therefore, the correct answer isA.

Using both mean and median helps identifyoutliers, such as very high executive salaries that skew the average. A large difference between the two indicates uneven distribution.

Thus, the correct answer isC.

APareto chartsorts data into categories and ranks them by frequency or impact. In data-driven decision making, this helps teams focus on the most significant contributors to a problem.

The chart combines bars and a cumulative line to highlight which factors account for the largest share of issues. This aligns with the Pareto principle and supports prioritization of improvement efforts.

Run charts track data over time, flowcharts describe processes, and cause charts are not a standard quality tool. Therefore, the correct answer isC.

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.

Ishikawa’sseven basic tools of qualitywere designed to be simple, visual, and accessible. In data-driven decision making, these tools help employees identify, analyze, and solve quality problems without requiring advanced statistical expertise.

The tools—such as flowcharts, histograms, Pareto charts, and cause-and-effect diagrams—represent processes graphically, making patterns and issues easier to understand. Additionally, they are intentionally designed so thatan average worker can easily understand and use them, supporting organization-wide quality improvement.

They do not rely on photographic representations, nor are they intended for advanced or expert-level training. Instead, they empower frontline employees to participate in continuous improvement efforts.

Therefore, the correct answers areA and C.

To determine the probability of achieving a specific monetary threshold, data-driven decision making relies onstandardization using the z-score. A z-score measures how many standard deviations a value is from the mean and allows analysts to calculate probabilities using the normal distribution.

In this scenario, the nonprofit wants to assess the likelihood that total donations will reach at least $50,000 given a known mean and standard deviation. The z-score enables conversion of the donation target into a standardized value, which can then be evaluated using probability tables or statistical software.

R-squared measures model fit in regression, the t-statistic is used in hypothesis testing, and the median does not support probability calculations. Therefore, the appropriate measure for determining probability in this context is thez-score, making optionDcorrect.

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.

To make a valid comparison in data-driven decision making, samples must becomparable and drawn from the same population, differing only in the factor being evaluated. In this case, the goal is to compare patient satisfaction between online telemedicine visits and in-person visits atFamily Practice A.

Usingonline Family Practice A telemedicine visits and in-person Family Practice A visitsensures that both samples come from the same organization, patient base, and survey methodology. This controls for external factors such as practice standards, demographics, and survey design, allowing differences in ratings to be attributed to the visit type rather than unrelated variables.

Comparing total visits to only one visit type introduces imbalance. Including other family practices introduces external variation and invalidates the comparison. Data-driven decision making stresses consistency and relevance in sample selection to ensure accurate conclusions.

Therefore, the correct answer isD, as it uses comparable samples that isolate the variable of interest.

Sample size is critical for ensuring **statistical significance** because it determines whether results can be confidently generalized to a larger population. In data-driven decision making, larger and appropriately selected samples reduce sampling error and increase the reliability of statistical estimates.

When sample sizes are too small, observed effects may be due to random variation rather than true underlying patterns. Larger samples provide more precise estimates of population parameters and increase the power of hypothesis tests, making it easier to detect meaningful differences or relationships.

While increasing sample size does not eliminate researcher bias, prevent hypothesis misinterpretation, or remove the need for further analysis, it strengthens the validity of conclusions. Statistical significance depends on sample size, effect size, and variability, all of which influence confidence in results.

Therefore, the correct answer is **A**, as adequate sample sizes allow accurate conclusions to be confidently applied to larger populations.

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