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Exploratory Data AnalysiseasyMultiple SelectObjective-mapped

MLS-C01 Exploratory Data Analysis Practice Question

Which TWO actions are appropriate when dealing with outliers in a dataset during exploratory data analysis? (Select TWO.)

⚠ Common exam trap

The MLS-C01 exam often tests the distinction between data transformation techniques (like log transformation) and data removal or replacement strategies, trapping candidates who think that simply changing a summary statistic (mean to median) or deleting outliers without investigation is a proper handling method.

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

Apply log transformation to reduce the impact of extreme values.

Applying a log transformation compresses the range of the data, reducing the influence of extreme values without removing them. This is a common technique in exploratory data analysis for right-skewed distributions, as it can make the data more normally distributed and improve the performance of models that assume normality.

Answer analysis

Option-by-option breakdown

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

  • Replace the mean with the median for numerical features.

    Why it's wrong here

    This does not handle outliers directly; consider transformations or robust methods.

  • Apply log transformation to reduce the impact of extreme values.

    Why this is correct

    Log transformation can compress skewed distributions and reduce outlier influence.

  • Remove all outliers without further investigation.

    Why it's wrong here

    Outliers may be valid data points; investigate before removal.

  • Use visualization techniques like box plots to identify outliers.

    Why this is correct

    Visualizations help understand the distribution and identify outliers.

  • Assume outliers are errors and delete them.

    Why it's wrong here

    Outliers may be genuine; deleting without analysis can lead to loss of information.

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Written by Johnson Ajibi, MSc IT Security

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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.