The answer is a box plot with interquartile range (IQR) to identify outliers. This method is correct because it uses the IQR, defined as Q3 minus Q1, to establish a lower fence at Q1 - 1.5*IQR and an upper fence at Q3 + 1.5*IQR; any data point falling outside these fences is flagged as an outlier. For the CompTIA Data+ DA0-001 exam, this question tests your ability to select the right visualization and statistical method for detecting extreme values in a distribution, especially when the goal is to highlight regions significantly below average. A common trap is choosing standard deviation or z-scores, which assume a normal distribution, while the IQR method is non-parametric and works for skewed data. Memory tip: think of the box plot’s “whiskers” as fences—anything beyond them is an outlier, with the 1.5 multiplier acting as the gatekeeper.
DA0-001 Communicating Data Insights Practice Question
This DA0-001 practice question tests your understanding of communicating data insights. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data analyst is creating a report on customer satisfaction scores across different regions. The analyst wants to highlight regions that are significantly below average. Which of the following statistical methods is most appropriate for identifying these outliers?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Box plot with interquartile range (IQR) to identify outliers.
A box plot with interquartile range (IQR) is the most appropriate method because it explicitly identifies outliers as data points falling below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. This directly addresses the analyst's goal of highlighting regions significantly below average, as the IQR method is a standard statistical technique for detecting extreme values in a distribution.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Bar chart with average line.
Why it's wrong here
Incorrect. Bar charts show values but do not statistically define outliers.
✗
Pie chart of satisfaction categories.
Why it's wrong here
Incorrect. Pie charts show proportions, not outlier detection.
✓
Box plot with interquartile range (IQR) to identify outliers.
Why this is correct
Correct. IQR-based box plots are a standard method for identifying statistical outliers.
Related concept
Read the scenario before looking for a memorised answer.
✗
Scatter plot of satisfaction vs. region.
Why it's wrong here
Incorrect. Scatter plots are for relationships, not outlier identification in a single variable.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may choose a bar chart with an average line (Option A) because it visually shows deviations, but it lacks a formal statistical criterion to define 'significantly below average,' which the IQR-based box plot provides.
Trap categories for this question
Command / output trap
Incorrect. Bar charts show values but do not statistically define outliers.
Detailed technical explanation
How to think about this question
The IQR method defines outliers as values more than 1.5 times the IQR below the first quartile (Q1) or above the third quartile (Q3), a rule based on Tukey's fences. This approach is robust to non-normal distributions and does not assume a specific data shape, making it ideal for real-world customer satisfaction data that may be skewed. In practice, a box plot also displays the median and quartiles, giving the analyst immediate visual context for how far below average a region's score must fall to be considered an outlier.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Communicating Data Insights — This question tests Communicating Data Insights — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Box plot with interquartile range (IQR) to identify outliers. — A box plot with interquartile range (IQR) is the most appropriate method because it explicitly identifies outliers as data points falling below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. This directly addresses the analyst's goal of highlighting regions significantly below average, as the IQR method is a standard statistical technique for detecting extreme values in a distribution.
What should I do if I get this DA0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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