The correct answer is to apply a log transformation. A skewness of 2.5 indicates a strong right-skewed distribution, where the tail extends toward higher values, and a log transformation compresses this tail by converting multiplicative relationships into additive ones, making the distribution more symmetric and reducing high kurtosis. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of how feature transformations affect distribution shape, a common data preprocessing step for models like linear regression that assume normality. A frequent trap is confusing scaling techniques—standardization and Min-Max scaling only change the range or mean, not skewness—while Box-Cox is a valid alternative but requires strictly positive data and is less direct for this scenario. Remember the memory tip: “Log for the long tail” to recall that log transformation is the go-to fix for right-skewed distributions.
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 uses Amazon QuickSight to visualize a dataset and observes that a numerical feature has a skewness of 2.5 and a kurtosis of 8. Which transformation should they apply to make the distribution more normal?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Apply a log transformation.
Option B is correct because a skewness of 2.5 indicates right skew, and a log transformation is commonly used to reduce skewness. Option A is incorrect because standardization does not change distribution shape. Option C is incorrect because Min-Max scaling does not change skewness. Option D is incorrect because a Box-Cox transformation requires positive data and is a more general solution, but log is simpler and often sufficient; however, Box-Cox is also valid. In the context of this question, log is the most direct answer.
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.
✗
Standardize the feature using Z-score normalization.
Why it's wrong here
Standardization does not change the shape of the distribution.
✗
Apply a Box-Cox transformation with lambda=0.5.
Why it's wrong here
Box-Cox with lambda=0.5 is a square root transformation, less effective for high skewness.
✗
Apply Min-Max scaling to the range [0,1].
Why it's wrong here
Min-Max scaling does not change distribution shape.
✓
Apply a log transformation.
Why this is correct
Log transformation reduces right skewness.
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.
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: Apply a log transformation. — Option B is correct because a skewness of 2.5 indicates right skew, and a log transformation is commonly used to reduce skewness. Option A is incorrect because standardization does not change distribution shape. Option C is incorrect because Min-Max scaling does not change skewness. Option D is incorrect because a Box-Cox transformation requires positive data and is a more general solution, but log is simpler and often sufficient; however, Box-Cox is also valid. In the context of this question, log is the most direct answer.
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.
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Question Discussion
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