|
|
GMAT Club Daily Prep
Thank you for using the timer - this advanced tool can estimate your performance and suggest more practice questions. We have subscribed you to Daily Prep Questions via email.
Customized
for You
Track
Your Progress
Practice
Pays
Not interested in getting valuable practice questions and articles delivered to your email? No problem, unsubscribe here.
11 Feb 2026, 01:06
Kudos
Bookmarks
Great question - this is a very common point of confusion in CR weaken questions!
Your logic is correct up to a point:
✓ Yes, we accept the premises as true
✓ Yes, the author IS comparing the same companies
✓ The ages ARE accurate
Here's where the key distinction lies:
In weaken questions, we accept the facts as true, but we attack whether those facts adequately support the conclusion.
Answer C doesn't say "the data is wrong." It says "the data has a limitation that makes it insufficient for the conclusion."
Let me show you exactly how this works:
The conclusion claims: "CEOs in general tend to be older now"
But the sample only includes companies that existed both now AND 20 years ago.
What's automatically excluded? Any company founded in the last 20 years - startups, newer tech companies, etc. These often have younger CEOs!
Simple analogy:
Imagine I survey only retirement homes and find people are older now than 20 years ago. True data! But can I conclude "people in general are older"? No - my sample is biased.
The Rule to Remember:
We accept FACTS as true. We attack whether those facts SUFFICIENTLY SUPPORT the conclusion.
Answer C reveals a sampling bias - the data is true but unrepresentative, so it cannot support a claim about "CEOs in general."
Answer: C
Your logic is correct up to a point:
✓ Yes, we accept the premises as true
✓ Yes, the author IS comparing the same companies
✓ The ages ARE accurate
Here's where the key distinction lies:
In weaken questions, we accept the facts as true, but we attack whether those facts adequately support the conclusion.
Answer C doesn't say "the data is wrong." It says "the data has a limitation that makes it insufficient for the conclusion."
Let me show you exactly how this works:
The conclusion claims: "CEOs in general tend to be older now"
But the sample only includes companies that existed both now AND 20 years ago.
What's automatically excluded? Any company founded in the last 20 years - startups, newer tech companies, etc. These often have younger CEOs!
Simple analogy:
Imagine I survey only retirement homes and find people are older now than 20 years ago. True data! But can I conclude "people in general are older"? No - my sample is biased.
The Rule to Remember:
We accept FACTS as true. We attack whether those facts SUFFICIENTLY SUPPORT the conclusion.
Answer C reveals a sampling bias - the data is true but unrepresentative, so it cannot support a claim about "CEOs in general."
Answer: C
chloreton
Moderators:
