To determine which statement about the samples is true, you need to consider how the samples were collected and whether the methods used are likely to result in biased samples.
Bias in Sampling:
- A sample is considered biased if it doesn't fairly represent the population it is intended to.
- If every individual in the population doesn't have an equal chance of being included in the sample, the sample could be biased.
Analyzing Sample 1:
- Sample 1 was collected by surveying every other person at sports practice after school.
- This method is likely biased because those attending sports practice may have different preferences than those who do not participate in sports. For example, students who attend sports practice might prefer more active or outdoor events, which might not represent the preferences of the entire student body.
Analyzing Sample 2:
- Sample 2 was collected by surveying every fifth person entering the cafeteria where all students eat.
- This method is less likely to be biased because the cafeteria is a common area where all students are present, thus giving a more representative cross-section of the student population. However, if the cafeteria is not accessible to all, or if there are particular times students attend the cafeteria, there could still be some bias.
Given the methods of survey collection:
- Sample 1 appears biased as it only includes students who attend sports practice.
- Sample 2 is designed to be more inclusive and representative of the entire student population.
Therefore, the most accurate statement about the samples is:
Sample 1 is biased.
