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Comparing Breathing Frequencies in Swimming. Researchers from the United Kingdom studied the effect of two breathing frequencies on both performance times and several physiological parameters in front crawl swimming. \({ }^{17}\) The breathing frequencies were one breath every second stroke (B2) and one breath every fourth stroke (B4). Subjects were 10 male collegiate swimmers. Each subject swam 200 meters, once with breathing frequency B2 and once on a different day with breathing frequency B4. (a) Describe the design of this matched pairs experiment, including the randomization required by this design. (b) Could this experiment be conducted using a completely randomized design? How would the design differ from the matched pairs experiment? (c) Suppose we allow each swimmer to choose his own breathing frequency and then 5 wim 200 meters using his selected frequency. Are there any problems with then comparing the performance of the two breathing frequencies?

Step by step solution

01

Understanding the Matched Pairs Design

The matched pairs design involves each participant acting as their own control, which in this case means each swimmer swims 200 meters twice: once with each breathing frequency (B2 and B4). The swimmers are compared against themselves to control for individual variability in swimming ability.

02

Incorporating Randomization

Randomization in a matched pairs design is achieved by randomizing the order in which each swimmer uses the two breathing frequencies. This could be done by flipping a coin for each swimmer to decide whether they will swim with B2 first or B4 first, helping to mitigate any ordering effects.

03

Exploring Completely Randomized Design

In a completely randomized design, swimmers would be randomly assigned to one of 2 groups: one using breathing frequency B2, and the other using B4. Each group would swim 200 meters, but different swimmers would be in different groups, unlike the matched pairs design where all swimmers participate under both conditions.

04

Discussing Problems with Self-Seleted Breathing Frequency

Allowing swimmers to choose their own breathing frequency introduces selection bias, as some swimmers may naturally perform better with the frequency they choose. This makes it difficult to determine if the frequency affects performance or if it's the swimmers' bias towards one frequency.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Matched Pairs Design

In a matched pairs design, every participant serves as their own point of comparison, which effectively means that each participant undergoes all conditions of the experiment. In the swimming study, each swimmer acts as their own control, swimming 200 meters with each breathing frequency: B2 (one breath every second stroke) and B4 (one breath every fourth stroke).
This design minimizes the impact of individual differences on the results because participants are compared to themselves rather than to other participants. This is particularly helpful when the number of participants is limited, as seen with only 10 swimmers taking part in this experiment.
By comparing each swimmer's performance using B2 and B4, any variation due to differences between participants is reduced, allowing a clearer assessment of how different breathing frequencies affect performance.

Randomization Techniques

Randomization is a key component in experimental design to eliminate biases. In a matched pairs design, this specifically involves randomizing the order in which treatments are applied. For the swimming experiment, each swimmer could start with either breathing frequency in a random order.
One practical way to randomize the order is to use something as simple as a coin flip for each swimmer to decide the sequence of breathing techniques. This step is crucial to reduce any potential fatigue or learning effects that could influence the results if all swimmers were to start with the same technique.
Randomization helps ensure that the different conditions in the study have an equal chance of being affected by extraneous variables, such as the time of day or specific individual conditions, which could otherwise skew the findings.

Selection Bias

Selection bias occurs when participants in a study are not representative of the general population because of how they are selected, which can lead to misleading conclusions.
In the scenario where swimmers choose their own breathing frequency, there's a risk of self-selection bias. If swimmers naturally pick the breathing rhythm they feel most comfortable with, it becomes difficult to determine if their performance is genuinely influenced by the breathing frequency or just a result of their preference.
This bias challenges the validity of the experiment as the internal validity is compromised. Ultimately, it may lead to overestimating the effectiveness of one technique over the other if swimmers perform better simply because they are more at ease with their chosen style.

Completely Randomized Design

A completely randomized design differs from matched pairs because participants are randomly assigned to separate groups, each of which experiences only one treatment condition. For the swimming experiment, a completely randomized design would mean dividing the swimmers into two groups: one using B2 and one using B4.
This type of design increases the generalizability of the results because it's not relying on each individual serving as their own control. However, it requires a sufficiently large sample size to ensure statistically meaningful results, which might be challenging with a limited number of participants like in this case, only 10 swimmers.
The lack of individual control in completely randomized designs can make it more difficult to attribute differences in outcomes directly to the treatments, as opposed to inherent differences between groups.