MCQ Collection
Data Visualization MCQs
Practice Data Visualization questions with answers and explanations.
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Correct Answer: B. A script preserves a reproducible record of the workflow
Explanation:
Saved code can be rerun, reviewed, and shared.
This is essential for reproducing data cleaning, analysis, and visualization steps.
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Correct Answer: C. Communicating a clear data-driven message
Explanation:
A chart should make the intended comparison or pattern easy to understand.
Decoration is secondary to accurate and efficient communication.
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Correct Answer: C. Saving the code and data-processing steps used to create each graph
Explanation:
Code records how data was transformed and how the chart was produced.
This allows others to recreate, audit, and update the result.
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Correct Answer: C. A meaningful ranking
Explanation:
Ordered factors represent categories such as low, medium, and high.
The order is meaningful even when distances between levels are not numeric.
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Correct Answer: C. The arithmetic mean
Explanation:
The arithmetic mean is the sum of the values divided by their number.
It uses every observation and is sensitive to extreme values.
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Correct Answer: D. Confirmatory analysis tests pre-specified hypotheses, while EDA searches for patterns
Explanation:
Confirmatory analysis evaluates questions defined before examining the evidence.
EDA is more open-ended and helps generate or refine hypotheses.
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Correct Answer: D. It directs attention to important values, events, or interpretations
Explanation:
Annotations help viewers notice the evidence that supports the message.
They are especially useful when a pattern is not immediately obvious.
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Correct Answer: D. head()
Explanation:
head() provides a quick view of the beginning of an object.
It helps verify column names and sample values without printing everything.
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Correct Answer: D. The median
Explanation:
The median depends on the ordered middle position rather than every magnitude.
A few extreme values therefore have limited influence on it.
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Correct Answer: A. It helps determine whether observed patterns are meaningful or plausible
Explanation:
Patterns can have different meanings in different subject areas.
Domain context helps distinguish useful signals from artifacts or impossible results.
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Correct Answer: A. Use redundant cues such as labels or shapes in addition to color
Explanation:
Color should not be the only way to distinguish important categories.
Labels, patterns, or shapes make the chart usable by more viewers.
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Correct Answer: A. The number of rows in df
Explanation:
nrow() reports the number of observations in a rectangular object.
Its companion ncol() reports the number of columns.