Question

A swimsuit manufacturer wants to test the speed of its newly designed suit. The company designs an experiment by having 6 randomly selected Olympic swimmers swim as fast as they can with their old swimsuit first and then swim the same event again with the new, expensive swimsuit. The company will use the difference in times as the response variable. Criticize the experiment and point out some of the problems with generalizing the results.

Short answer

The experiment has selection bias, sequence effects, lack of blinding, uncontrolled conditions, and limited trials.

Step-by-step solution

Selection Bias

The experiment uses only 6 randomly selected Olympic swimmers. This small sample size and specific group may not represent the general population, causing selection bias. Olympic swimmers may have different performance characteristics compared to regular swimmers, limiting the applicability of the results to non-Olympians.

Sequence Effect

The swimmers use the old swimsuit first followed by the new swimsuit. This sequence may introduce fatigue or learning effects, influencing the results. To mitigate this, a counterbalanced design where half the swimmers start with the new swimsuit could be considered.

Lack of Blinding

Swimmers are aware of which suit they are wearing. This lack of blinding may introduce performance bias, as they might unintentionally swim better or worse based on their expectations of the suit's performance.

External Conditions

The conditions such as water temperature, pool conditions, or swimmer's health can vary between the two swims. These factors should be controlled or accounted for to ensure that differences in times are due to the swimsuits.

Limited Trials

Each swimmer only swims once in each swimsuit, which does not account for variability in performance across multiple trials. More trials would provide a more reliable measure of performance differences.

Key concepts

Selection Bias

In the context of experimental design, selection bias occurs when the participants selected for a study are not representative of the general population to which you want to apply your findings. In the swimsuit manufacturer's experiment, using only six Olympic swimmers might result in selection bias. This small and specialized group may not reflect how the average swimmer would perform with the new swimwear. Additionally, Olympic athletes might have unique characteristics, such as enhanced training and technique, that make their performance differ substantially from that of regular swimmers. To minimize selection bias, researchers should strive to include a more diverse and larger sample that can capture the variability present in the broader population. This ensures that the study's results are more generalizable and applicable to the target market of the swimsuits, which might include amateur swimmers and enthusiasts as well.

Sequence Effect

The sequence effect is a common issue in experimental design, arising when the order in which treatments are administered influences the outcomes. In this experiment, swimmers first used their old swimsuit and then the new one. This setup can cause a sequence effect. Possible issues include fatigue, since the swimmers might be tired during the second swim, affecting their performance. Another possibility is a learning effect, where swimmers improve simply because they are repeating the task.
To counter sequence effects, researchers could use a counterbalanced design. By having half the participants start with the new swimsuit and the other half with the old one, researchers can effectively balance out any sequence-related influences on the results. This ensures that observed differences are more likely due to the swimwear itself, rather than the order of use.

Blinding in Experiments

Blinding is a crucial method in experiments to reduce bias. In this experiment, there is a lack of blinding because swimmers know which swimsuit they are wearing. This awareness can lead to performance bias, where swimmers unconsciously alter their efforts based on their expectations of the suits. For instance, knowing that they are wearing a new, supposedly superior swimsuit, swimmers might inadvertently push themselves harder, skewing the results.
To address this, experiments can use single or double blinding methods. In single blinding, participants are unaware of which treatment they are receiving. This can be challenging in garment testing, but efforts can be made, such as disguising the feel of the swimsuit materials. In double blinding, both participants and the researchers handling the experiment are unaware of the treatment assignments, further minimizing bias and ensuring a more objective assessment of the swimwear’s impact.

Controlled Variables in Experiments

Controlled variables are aspects of an experiment that are kept constant to make sure that any changes in the dependent variable are due to the independent variable. In the swimsuit test, several external factors could affect the swimmers' performances, such as water temperature, pool conditions, and the swimmers' health or mental state between swims.
To ensure a fair test, all these conditions should be controlled as much as possible. This means conducting the swims under the same environmental conditions for each test. Researchers could go further by checking the swimmers' health and fitness levels before both swim sessions to exclude any variability arising from these factors. By controlling these variables, the experiment's integrity is upheld, ensuring that any recorded differences in swim times are genuinely due to the changes in swimwear, rather than external or fluctuating conditions.