- A
Build a scatterplot matrix to visualize pairwise relationships
Why wrong: Scatterplot matrix shows relationships but not missing values or outliers directly.
- B
Use histograms to visualize the distribution of each numerical feature
Histograms reveal outliers, skewness, and missing data patterns (e.g., zero counts).
- C
Plot a confusion matrix to assess class separation
Why wrong: Confusion matrix is for evaluating classification model predictions, not for EDA.
- D
Create a correlation matrix to identify redundant features
Why wrong: Correlation matrix does not show missing values or outliers directly.
- E
Generate summary statistics using df.describe() in a SageMaker notebook
df.describe() provides count, mean, std, min, max, which help identify missing values and outliers.
Quick Answer
The correct actions are generating summary statistics with df.describe() and visualizing distributions with histograms. Summary statistics provide a quick quantitative overview of each column, including count, mean, standard deviation, min, and max, which directly reveal missing values through reduced counts and flag potential outliers through extreme min or max values. Histograms complement this by offering a visual representation of the data’s distribution, making skewness, gaps, and outliers immediately apparent. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of foundational exploratory data analysis techniques within SageMaker notebooks, often as a first step before any modeling. A common trap is confusing a correlation matrix or scatterplot matrix for data quality assessment—these tools reveal relationships, not missing values or outliers. Memory tip: think “stats for counts, histograms for shapes” to remember that df.describe() handles the numbers while histograms handle the visual patterns.
MLS-C01 Exploratory Data Analysis Practice Question
This MLS-C01 practice question tests your understanding of exploratory data analysis. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 scientist is using Amazon SageMaker to perform exploratory data analysis on a dataset with missing values and outliers. Which TWO actions should the scientist take to understand the data quality? (Choose TWO.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use histograms to visualize the distribution of each numerical feature
Option A is correct because generating summary statistics helps identify missing counts and outliers via min/max. Option D is correct because visualizing distributions with histograms helps spot outliers and skewness. Option B is wrong because a correlation matrix does not directly show missing values or outliers. Option C is wrong because a confusion matrix is for classification models, not for data exploration. Option E is wrong because a scatterplot matrix shows pairwise relationships, not missing values.
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.
- ✗
Build a scatterplot matrix to visualize pairwise relationships
Why it's wrong here
Scatterplot matrix shows relationships but not missing values or outliers directly.
- ✓
Use histograms to visualize the distribution of each numerical feature
Why this is correct
Histograms reveal outliers, skewness, and missing data patterns (e.g., zero counts).
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Plot a confusion matrix to assess class separation
Why it's wrong here
Confusion matrix is for evaluating classification model predictions, not for EDA.
- ✗
Create a correlation matrix to identify redundant features
Why it's wrong here
Correlation matrix does not show missing values or outliers directly.
- ✓
Generate summary statistics using df.describe() in a SageMaker notebook
Why this is correct
df.describe() provides count, mean, std, min, max, which help identify missing values and outliers.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Similar concept trap
Confusion matrix is for evaluating classification model predictions, not for EDA.
Command / output trap
Scatterplot matrix shows relationships but not missing values or outliers directly.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Exploratory Data Analysis — study guide chapter
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use histograms to visualize the distribution of each numerical feature — Option A is correct because generating summary statistics helps identify missing counts and outliers via min/max. Option D is correct because visualizing distributions with histograms helps spot outliers and skewness. Option B is wrong because a correlation matrix does not directly show missing values or outliers. Option C is wrong because a confusion matrix is for classification models, not for data exploration. Option E is wrong because a scatterplot matrix shows pairwise relationships, not missing values.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 20, 2026
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
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