Quick Answer
The correct answer is homoscedasticity, as the violation described—increasing residual variance with higher advertising spend—is the textbook definition of heteroscedasticity. In linear regression, homoscedasticity requires that the residuals have constant variance across all levels of the independent variable; when this assumption is broken, the model’s predictions become unreliable, especially at extreme values. On the CompTIA AI+ AI0-001 exam, this concept tests your ability to distinguish between the four core regression assumptions: linearity, independence, normality, and homoscedasticity. A common trap is confusing heteroscedasticity with non-linearity, but remember that linearity concerns the shape of the relationship, not the spread of errors. To lock in the concept, use the mnemonic “Homo means same, Hetero means different”—if the residual spread changes, you’ve violated homoscedasticity.
This AI0-001 practice question tests your understanding of machine learning and deep learning. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 company uses linear regression to predict sales based on advertising spend. The model's residuals show a pattern of increasing variance as spend increases. Which assumption of linear regression is violated?
Normality
Why wrong: Normality concerns the distribution shape, not variance consistency.
Homoscedasticity
Homoscedasticity requires constant variance of residuals; increasing variance violates it.
Linearity
Why wrong: Linearity assumption is about the functional form, not residual variance.
Independence
Why wrong: Independence refers to errors being uncorrelated, not variance pattern.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Homoscedasticity
Option D is correct because homoscedasticity assumes constant variance of residuals; increasing variance indicates heteroscedasticity. Option A is incorrect because linearity is about the relationship, not residual variance. Option B is incorrect because independence refers to errors being independent. Option C is incorrect because normality is about the distribution of residuals, not variance.
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
For each option: why learners choose it and why it is or isn't the right answer here.
Normality
Why it's wrong here
Normality concerns the distribution shape, not variance consistency.
Homoscedasticity
Why this is correct
Homoscedasticity requires constant variance of residuals; increasing variance violates it.
Related concept
Static NAT maps one inside address to one outside address.
Linearity
Why it's wrong here
Linearity assumption is about the functional form, not residual variance.
Independence
Why it's wrong here
Independence refers to errors being uncorrelated, not variance pattern.
Common exam traps
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
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.
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
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
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 AI0-001 NAT questions on configuration and troubleshooting.
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FAQ
Machine Learning and Deep Learning — This question tests Machine Learning and Deep Learning — Static NAT maps one inside address to one outside address..
The correct answer is: Homoscedasticity — Option D is correct because homoscedasticity assumes constant variance of residuals; increasing variance indicates heteroscedasticity. Option A is incorrect because linearity is about the relationship, not residual variance. Option B is incorrect because independence refers to errors being independent. Option C is incorrect because normality is about the distribution of residuals, not variance.
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 AI0-001 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 23, 2026
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.
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