The 10% condition is generally applied in statistical sampling to ensure that the sample size is small enough relative to the population size, such that sampling without replacement is effectively the same as sampling with replacement. The rule states that the sample size should be no more than 10% of the population size.
Let's evaluate the scenarios:
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A sample of 40 to represent the number of people on a bus: This doesn't specifically mention the population size of the bus riders, but generally buses do not have a large population size (typically less than 400). Therefore, it's likely that this scenario does not violate the 10% condition.
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A population of 1,200 and a sample of 600: Here, the sample size (600) is 50% of the population (1,200), which violates the 10% condition.
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A population of 2,000 and a sample of 100: The sample size (100) is 5% of the population (2,000), which satisfies the 10% condition.
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A sample of 10 to represent the number of students in a classroom: As classrooms typically have a small population (often less than 100 students), this scenario would likely satisfy the 10% condition, assuming the number of students is indeed larger than 10.
Based on this evaluation, the scenarios that apply the 10% condition are the population of 2,000 and a sample of 100, as well as the sample of 10 to represent the number of students in a classroom (assuming there are enough students in the class).
Thus, the best answer to select based on the provided options is:
- A population of 2,000 and a sample of 100.