The 10% condition typically applies in statistical sampling when you are sampling without replacement. The condition states that if your sample size is less than 10% of the population size, the sampling can be considered as approximately independent.
Let's evaluate each option:
-
A sample of 150 out of 300 participants:
- Sample size = 150, Population size = 300
- 150 is 50% of 300, which is greater than 10%.
-
A sample of 65 out of 675 apples:
- Sample size = 65, Population size = 675
- 65 is about 9.63% of 675, which is less than 10%.
-
A sample of 200 out of 1,000 athletes:
- Sample size = 200, Population size = 1,000
- 200 is 20% of 1,000, which is greater than 10%.
-
A sample of 10 out of 80 students:
- Sample size = 10, Population size = 80
- 10 is 12.5% of 80, which is greater than 10%.
From the above evaluations, the scenario where the 10% condition applies is:
A sample of 65 out of 675 apples.