- A
Min-max normalization
Why wrong: Min-max scaling preserves the relative distances and does not reduce outlier influence.
- B
Box-Cox transformation
Why wrong: Box-Cox assumes positive values and may not adequately handle extreme outliers.
- C
Rank transformation
Rank transformation replaces values with their rank order, making the distribution uniform and robust to outliers.
- D
Log transformation
Why wrong: Log transformation reduces skew but large outliers still have a significant impact.
Quick Answer
The correct answer is rank transformation. This technique works by replacing each value in the target variable with its rank order within the dataset, which completely removes the influence of extreme outliers while perfectly preserving the relative order of observations. For a regression problem with a long-tail distribution, this transformation is ideal because it treats the outlier as just another data point in the sorted sequence, eliminating its leverage on the model without distorting the underlying ranking. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of how different transformations handle outlier influence—a common trap is choosing log or Box-Cox transformations, which reduce skew but still allow extreme values to affect the regression coefficients. Remember that rank transformation is the only option here that discards magnitude entirely to focus solely on order. Memory tip: think “rank = rank order, not magnitude” to avoid confusing it with scaling or power transforms.
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 machine learning engineer is analyzing a dataset for a regression problem. The target variable has a long-tail distribution with extreme outliers. The engineer wants to reduce the influence of outliers while preserving the relative order of values. Which data transformation should the engineer apply to the target variable?
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
Rank transformation
Option B is correct because the rank transformation maps values to their ranks, eliminating the impact of outliers while preserving order. Option A is wrong because Box-Cox requires positive values and may not reduce outlier influence. Option C is wrong because log transformation can reduce skew but still allows outliers to remain influential. Option D is wrong because min-max scaling does not reduce outlier influence; it compresses the range.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Min-max normalization
Why it's wrong here
Min-max scaling preserves the relative distances and does not reduce outlier influence.
- ✗
Box-Cox transformation
Why it's wrong here
Box-Cox assumes positive values and may not adequately handle extreme outliers.
- ✓
Rank transformation
Why this is correct
Rank transformation replaces values with their rank order, making the distribution uniform and robust to outliers.
Related concept
Static NAT maps one inside address to one outside address.
- ✗
Log transformation
Why it's wrong here
Log transformation reduces skew but large outliers still have a significant impact.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
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Exploratory Data Analysis — study guide chapter
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Exploratory Data Analysis practice questions
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Rank transformation — Option B is correct because the rank transformation maps values to their ranks, eliminating the impact of outliers while preserving order. Option A is wrong because Box-Cox requires positive values and may not reduce outlier influence. Option C is wrong because log transformation can reduce skew but still allows outliers to remain influential. Option D is wrong because min-max scaling does not reduce outlier influence; it compresses the range.
What should I do if I get this MLS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 2026
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.
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