The answer is to apply a log transformation to the target variable. This is correct because the increasing residual spread with predicted values is classic heteroscedasticity, which violates the ordinary least squares assumption of constant variance; a log transform compresses the scale of large values, stabilizing the variance and making the residuals more homoscedastic. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of regression diagnostics and remedial measures—a common trap is confusing heteroscedasticity with non-linearity and choosing polynomial features or interactions, which address shape, not variance. A key memory tip: when residuals fan out like a trumpet, think “log the target” to tame the spread.
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 is building a regression model to predict house prices. The dataset includes features such as square footage, number of bedrooms, and location. After training a linear regression model, the scientist notices that the residuals have a pattern: they increase as the predicted value increases. Which action is most appropriate?
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 to the target variable
Patterned residuals (heteroscedasticity) violating linear regression assumptions. Log-transforming the target variable can stabilize variance. Adding polynomial features or interactions may help with non-linearity but not specifically for heteroscedasticity. Ridge regression is for multicollinearity, not for patterned residuals.
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.
✗
Remove outliers from the dataset
Why it's wrong here
Outliers may cause patterns but not necessarily the increasing variance pattern described.
✗
Use Ridge regression instead of linear regression
Why it's wrong here
Ridge regression addresses multicollinearity, not patterned residuals.
✗
Add polynomial features to the model
Why it's wrong here
Polynomial features address non-linearity, not heteroscedasticity.
✓
Apply a log transformation to the target variable
Why this is correct
Log transformation can stabilize variance and reduce heteroscedasticity.
Related concept
Static NAT maps one inside address to one outside address.
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.
Modeling — This question tests Modeling — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Apply a log transformation to the target variable — Patterned residuals (heteroscedasticity) violating linear regression assumptions. Log-transforming the target variable can stabilize variance. Adding polynomial features or interactions may help with non-linearity but not specifically for heteroscedasticity. Ridge regression is for multicollinearity, not for patterned residuals.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.