If a garden does not receive

Answer choices

1. A

   Never a Flaw4% picked this

   fails to specify adequately the meaning in context of the

   There's never been a correct answer that demands a specific measurement or quantity or definition, or forces us to name specifically who our sources are. We know what "ideal" means = best possible.

   4%
2. B

   Wrong Flaw4% picked this

   infers a cause from a

   This refers to the famous Causal Flaw, but there's no correlation in the evidence. A correlation would sound like "gardens that don't get plenty of water and sunlight and aren't planted in rich soil are less likely than those who do to be productive".

   4%
3. C

   Never Correct / Wrong Flaw2% picked this

   confuses a cause with its

   This also refers to Causal Flaws, but this answer is never correct. We can suggest to an author that they have possibly become too convinced of one causal possibility, where others exist ("fails to consider that a given causal relationship may be occurring in reverse"), but we are never allowed to act like we know the "right" version of causality. Otherwise, we'd be duplicating the author's flaw.

   2%
4. D

   Correct90% picked this

   takes a set of necessary conditions

   Why this is right

   Any time we see the Necessary vs. Sufficient answer choice, we can just ask ourselves, "Was there conditional logic in the argument?" If so, there's a 90% or better chance that's the right answer. If not, there's a 0% chance it's the right answer. A productive garden requires plenty of water and sunlight and rich soil. Meanwhile, this author acts like since we know that Patricia has met those three requirements that her garden therefore will be productive. So the author is acting like those three requirements are sufficient to guarantee a productive garden.

   Skill tested: Flaw · how this choice captures the argument's function is the move to repeat next time.

   90%
5. E

   Wrong Flaw0% picked this

   relies on a sample that is unlikely to

   This refers to the famous Sampling flaw, in which we're nervous about an author relying on a sample because it's too small, unrepresentative, or self-selecting.

   0%