Jessica polled the last 86 athletes to finish a bike race.Is this sample of the athletes in the bike race likely to be biased?yesnoSubmit

To determine whether Jessica's sample of the last 86 athletes to finish a bike race is likely to be biased, we need to consider a few factors:

1. Sampling Method: The method used to select the athletes can introduce bias. If Jessica only surveyed those who finished last, she may not accurately represent the entire population of athletes, especially those who finished earlier. Finishing position could correlate with various factors, such as skill level, experience, or physical condition.

2. Time Frame: Polling only those who finished at the end may omit insights from varying performance levels and backgrounds. This can skew the results since those who finish last may have different motivations, experiences, or demographics compared to those who finished at the front.

3. Sample Size: While 86 is a decent sample size, it is essential to consider who is being sampled. The characteristics of the last finishers might not reflect the broader group of participants.

4. Diversity: A sample should capture a range of demographics and abilities to be effective. If the last finishers are of a similar background, this can lead to a biased outcome.

Therefore, considering these factors, the answer is Yes, this sample of athletes in the bike race is likely to be biased.