The 10% condition is a rule of thumb used in statistics that states that when sampling without replacement, the sample size should be no more than 10% of the population size in order for the sampling distribution to be approximately normal.
Let's evaluate the scenarios:
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A population of 1,200 and a sample of 600:
- Sample size (600) is 50% of the population size (1,200).
- Does not satisfy the 10% condition.
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A population of 2,000 and a sample of 100:
- Sample size (100) is 5% of the population size (2,000).
- Satisfies the 10% condition.
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A sample of 10 to represent the number of students in a classroom:
- Without specific information about the population size, we can't determine the 10% condition.
- Cannot assess.
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A sample of 40 to represent the number of people on a bus:
- Similarly, we need the population size to determine if the 10% condition applies.
- Cannot assess.
Based on the evaluations, only scenario 2 (the population of 2,000 and a sample of 100) satisfies the 10% condition.