Bytelearn - cat image with glassesAI tutor

Welcome to Bytelearn!

Let’s check out your problem:

Each of these relationships reflects a correlation. Which relationship most likely reflects correlation but not causation?\newlineChoices:\newline(A) Riding a bicycle more often is associated with stronger leg muscles.\newline(B) Riding a bicycle more often is associated with hiking more often.\newline(C) Riding a bicycle more often is associated with wearing a helmet more often.

Full solution

Q. Each of these relationships reflects a correlation. Which relationship most likely reflects correlation but not causation?\newlineChoices:\newline(A) Riding a bicycle more often is associated with stronger leg muscles.\newline(B) Riding a bicycle more often is associated with hiking more often.\newline(C) Riding a bicycle more often is associated with wearing a helmet more often.
  1. Analyze Relationship of Option (A): Analyze the relationship of option (A): Does riding a bicycle more often cause stronger leg muscles? The answer could be Yes, as stronger leg muscles could be a result of the physical exercise that comes with riding a bicycle.
  2. Analyze Relationship of Option (B): Analyze the relationship of option (B): Does riding a bicycle more often cause someone to hike more often? The answer is not necessarily, as these are two different activities that don't cause each other, but people who enjoy outdoor activities might tend to do both.
  3. Analyze Relationship of Option (C): Analyze the relationship of option (C): Does riding a bicycle more often cause someone to wear a helmet more often? The answer is Yes, as wearing a helmet is a safety measure that is likely to be taken by someone who rides a bicycle frequently.
  4. Select Most Likely Option: Finally, select the option that most likely reflects correlation but not causation. The answer is 'Riding a bicycle more often is associated with hiking more often.' as the two activities are correlated due to similar interests in outdoor activities but one does not cause the other.

More problems from Correlation and causation