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MLS-C01 Exploratory Data Analysis Practice Question

Which THREE of the following are common issues that can be identified during exploratory data analysis? (Select THREE.)

⚠ Common exam trap

The MLS-C01 exam often tests the boundary between data-level issues (EDA) and model training issues, so candidates mistakenly select gradient vanishing (a deep learning optimization problem) or API latency (an operational concern) as EDA findings.

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

Multicollinearity between features

Multicollinearity occurs when two or more features in a dataset are highly correlated, meaning they contain redundant information. During exploratory data analysis (EDA), correlation matrices and variance inflation factor (VIF) calculations can reveal this issue, which can destabilize linear regression models and inflate coefficient standard errors.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Multicollinearity between features

    Why this is correct

    High correlation between features can be detected via correlation matrix.

  • High latency in API endpoints

    Why it's wrong here

    Latency is a performance metric, not a data characteristic.

  • Gradient vanishing in neural networks

    Why it's wrong here

    Gradient vanishing is a training issue, not a data issue.

  • Class imbalance in the target variable

    Why this is correct

    Imbalanced classes are identified by examining target distribution.

  • Missing values in features

    Why this is correct

    Missing data is a common data quality issue detected during EDA.

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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.