If two attributes have a strong positive correlation, increasing one will likely increase the other.

• A. True
• B. False
• C. Always
• D. Not necessarily

Answer: (D)

Correlation describes how two attributes move together in the data, not what happens if you actively change one of them. A strong positive correlation means the variables tend to rise together in observations, but it doesn’t prove that increasing one will cause the other to increase. There could be a hidden third factor driving both, the relationship might not hold under intervention, or it could vary in different ranges. So, the best answer is Not necessarily—the observed association does not guarantee a causal effect.

Choosing “Always” would imply a guaranteed causal link, which isn’t warranted. “True” would wrongly assert causation, and “False” would deny any association, which isn’t accurate given the observed correlation.