For a baobab tree habitat in South Africa, a scientist randomly selected 50 baobab trees that were 17 years old...

1. TRANSLATE the study design information

• Given information:
  • 50 baobab trees randomly selected
  • Trees were 17 years old
  • Selected from a baobab tree habitat in South Africa
  • Random assignment to two watering treatments

• What this tells us: We have a random sample from a specific population, followed by random assignment to treatment groups.

2. INFER the generalizability principle

• Key statistical rule: Results can only be generalized to the population from which the sample was randomly selected
• The random assignment allows us to infer causation within our sample
• But generalization depends entirely on the original population sampled

3. INFER the source population

• The sample was randomly selected from: 'baobab trees that were 17 years old in this habitat'
• This defines our target population for generalization
• Results cannot extend beyond this specific group

4. TRANSLATE answer choices to population scope

• Choice A: Just the 50 trees (sample, not population)
• Choice B: 19-year-old trees (wrong age group)
• Choice C: All 17-year-old trees in South Africa (too broad)
• Choice D: All 17-year-old trees in this habitat (matches source population)

Answer: D

Why Students Usually Falter on This Problem

Most Common Error Path:

Weak INFER skill: Students confuse the scope of generalization and select Choice C, thinking results apply to all 17-year-old baobab trees in South Africa.

The reasoning error: 'Since the trees are in South Africa and the study worked with 17-year-old trees, the results must apply to all 17-year-old trees in the country.' This misses that the sample was drawn from only one specific habitat, not from all habitats across South Africa.

This may lead them to select Choice C (All the baobab trees that were 17 years old in South Africa)

Second Most Common Error:

Poor TRANSLATE reasoning: Students focus on the treatment groups rather than the sampling method and select Choice A.

The reasoning error: 'The study can only tell us about the 50 trees that were actually studied.' This misunderstands the purpose of random sampling, which is specifically designed to allow generalization beyond just the sample.

This may lead them to select Choice A (All the 50 baobab trees that were selected in this habitat)

The Bottom Line:

Statistical generalizability requires careful attention to the sampling method and source population. Random sampling enables generalization, but only to the population from which the sample was drawn - no broader, no narrower.