Question 15·Hard·Evaluate Statistical Claims: Observational Studies and Experiments
A nutritionist wants to test whether consuming a new energy gel improves 5-kilometer (5K) race times. The nutritionist recruits 60 volunteer runners from a local running club and randomly assigns 30 of them to consume the gel 15 minutes before running a timed 5K race; the other 30 runners consume a placebo that looks and tastes identical. Immediately after the race, the nutritionist compares the finish times of the two groups.
Which conclusion about the energy gel is most appropriate based on this study design?
For questions about what conclusions are appropriate, first classify the study: randomized experiment (researcher assigns treatments) or observational study (researcher only watches). Remember the key rules: randomized experiments support cause‑and‑effect conclusions for the studied subjects; random samples support generalizing results to the larger population they were sampled from. Then, separately answer these two questions—(1) causation vs association, and (2) can vs cannot generalize—and choose the option whose two parts match your decisions exactly.
Hints
Identify the study type
Look at how the gel and placebo are given out. Does the nutritionist just observe what runners do, or does the nutritionist randomly assign who gets what?
Connect study type to what you can conclude
Once you know if it’s an experiment or an observational study, recall: which type allows cause-and-effect conclusions, and which type only shows association?
Think about the population you can generalize to
Were the 60 runners randomly selected from all runners, or are they a specific group (like volunteers from one club)? How does that affect whether you can apply the results to all runners?
Match the two decisions to the answer choices
Decide: (1) cause‑and‑effect vs only association, and (2) can vs cannot generalize to all runners. Then pick the choice whose two parts match your decisions.
Step-by-step Explanation
Classify the study: experiment or observational study?
Ask: Did the nutritionist assign treatments or just observe what runners chose on their own?
Here, the nutritionist randomly assigns 30 runners to consume the gel and 30 to consume a placebo before the race. Because the researcher controls and randomly assigns the treatment, this is a randomized experiment, not an observational study.
Decide if cause-and-effect is justified
Randomized experiments, when well designed, allow us to make cause-and-effect conclusions for the subjects in the experiment.
Because the runners were randomly assigned to gel versus placebo, differences in average 5K times between the two groups can reasonably be attributed to the gel (rather than to pre-existing differences between the groups). So we can make a cause‑and‑effect conclusion for the runners in this study.
Decide if results can be generalized to all runners
To generalize results to a larger population (like all runners), we usually need a random sample from that population.
In this study, the 60 runners are volunteers from a local running club, not a random sample of all runners. They may differ from other runners in age, fitness, training level, etc. So the study does not support automatically generalizing the results to all runners.
Match the correct combination to the answer choices
From the reasoning:
- We can make a cause‑and‑effect conclusion about the gel’s effect on 5K times, but only for the runners in this study.
- We cannot necessarily generalize these results to all runners, because the sample is not a random sample from all runners.
The answer choice that states this combination is:
D) A cause-and-effect conclusion about the gel’s effect on 5K times can be made for the runners in this study, but the results cannot necessarily be generalized to all runners.