The answer is box plots grouped by target, histograms, and KDE plots. These three techniques are effective because they directly compare the distribution of the continuous feature across the two classes of the binary target, revealing differences in central tendency, spread, and modality. When visualizing a continuous feature against a binary target, the goal is to assess separation or overlap between the groups, which these plots accomplish by showing density or quartile-based summaries. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this concept tests your understanding of exploratory data analysis (EDA) for classification problems, often appearing in scenario-based questions where you must choose appropriate plots. A common trap is selecting a scatter plot, which requires two continuous variables, or a bar chart, which is for categorical features. Remember the memory tip: “Box, Hist, KDE—three ways to see two groups clearly.”
MLS-C01 Exploratory Data Analysis Practice Question
This MLS-C01 practice question tests your understanding of exploratory data analysis. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 performing EDA on a dataset with a binary target variable. Which THREE techniques can help assess the relationship between a continuous feature and the target?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
KDE plot grouped by target
Box plots (comparing distributions for each class), histograms (overlay or side-by-side), and KDE plots (probability density) are all effective for visualizing the relationship between a continuous feature and a binary target. Option D (scatter plot) requires two continuous variables. Option E (bar chart) is for categorical features.
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.
✗
Scatter plot against another continuous feature
Why it's wrong here
Scatter plots show relationship between two continuous variables, not directly with target.
✓
KDE plot grouped by target
Why this is correct
KDE plots show smoothed density per class.
Related concept
Read the scenario before looking for a memorised answer.
✓
Histogram colored by target
Why this is correct
Histograms can compare distributions per class.
Related concept
Read the scenario before looking for a memorised answer.
✗
Bar chart of feature values
Why it's wrong here
Bar charts are for categorical features.
✓
Box plot grouped by target
Why this is correct
Box plots show distribution differences between classes.
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
Command / output trap
Scatter plots show relationship between two continuous variables, not directly with target.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
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: KDE plot grouped by target — Box plots (comparing distributions for each class), histograms (overlay or side-by-side), and KDE plots (probability density) are all effective for visualizing the relationship between a continuous feature and a binary target. Option D (scatter plot) requires two continuous variables. Option E (bar chart) is for categorical features.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data scientist is performing EDA on a dataset with both numeric and categorical features. Which TWO techniques are appropriate for visualizing the relationship between a numeric feature and a binary categorical target?
medium
A.Histogram
B.Stacked bar chart
✓ C.Violin plot grouped by target
✓ D.Box plot grouped by target
E.Scatter plot
Why C: Option A (box plot) shows distribution of a numeric feature across categories. Option C (violin plot) combines box plot and density. Option B is wrong because bar charts are for categorical vs categorical. Option D is wrong because histograms show distribution of a single variable. Option E is wrong because scatter plots are for two numeric variables.
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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.
Question Discussion
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