MLS-C01 Exploratory Data Analysis Practice Question
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
Histograms show the distribution of numerical features, helping to identify skewness and outliers. Option E is correct because summary statistics like df.describe() provide count, mean, min, max, and quartiles, which reveal missing values (via count) and outliers (via min/max). Option A is incorrect because a scatterplot matrix visualizes pairwise relationships but does not directly show missing values or outliers. Option C is incorrect because a confusion matrix is used for evaluating classification model performance, not for data exploration. Option D is incorrect because a correlation matrix shows relationships between features but does not highlight missing values or outliers.
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).
- ✗
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.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.